Overview | Package | Class | Use | Tree | Deprecated | Index | Help
PREV NEXT | FRAMES NO FRAMES

A B C D E F G H I K L M N O P R S T U V W

## A

ADDITIVE_MODE - Static variable in class org.apache.commons.math.util.ResizableDoubleArray
  additive expansion mode
AbstractContinuousDistribution - class org.apache.commons.math.distribution.AbstractContinuousDistribution.
  Base class for continuous distributions.
AbstractContinuousDistribution() - Constructor for class org.apache.commons.math.distribution.AbstractContinuousDistribution
  Default constructor.
AbstractDistribution - class org.apache.commons.math.distribution.AbstractDistribution.
  Base class for probability distributions.
AbstractDistribution() - Constructor for class org.apache.commons.math.distribution.AbstractDistribution
  Default constructor.
AbstractIntegerDistribution - class org.apache.commons.math.distribution.AbstractIntegerDistribution.
  Base class for integer-valued discrete distributions.
AbstractIntegerDistribution() - Constructor for class org.apache.commons.math.distribution.AbstractIntegerDistribution
  Default constructor.
AbstractStorelessUnivariateStatistic - class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic.
  Abstract Implementation for the `StorelessUnivariateStatistic` interface.
AbstractStorelessUnivariateStatistic() - Constructor for class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
AbstractUnivariateStatistic - class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic.
  Abstract base class for all implementations of the `UnivariateStatistic` interface.
AbstractUnivariateStatistic() - Constructor for class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
abs() - Method in class org.apache.commons.math.complex.Complex
  Return the absolute value of this complex number.
absoluteAccuracy - Variable in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Maximum absolute error.
acos(Complex) - Static method in class org.apache.commons.math.complex.ComplexUtils
  Compute the inverse cosine for the given complex argument.
add(Complex) - Method in class org.apache.commons.math.complex.Complex
  Return the sum of this complex number and the given complex number.
add(BigMatrix) - Method in interface org.apache.commons.math.linear.BigMatrix
  Compute the sum of this and m.
add(BigMatrix) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Compute the sum of this and `m`.
add(RealMatrix) - Method in interface org.apache.commons.math.linear.RealMatrix
  Compute the sum of this and m.
add(RealMatrix) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Compute the sum of this and `m`.
addData(double, double) - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Adds the observation (x,y) to the regression data set.
addData(double[][]) - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Adds the observations represented by the elements in `data`.
addElement(double) - Method in interface org.apache.commons.math.util.DoubleArray
  Adds an element to the end of this expandable array
addElement(double) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Adds an element to the end of this expandable array.
addElementRolling(double) - Method in interface org.apache.commons.math.util.DoubleArray
  Adds an element to the end of the array and removes the first element in the array.
addElementRolling(double) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Adds an element to the end of the array and removes the first element in the array.
addValue(Object) - Method in class org.apache.commons.math.stat.Frequency
  Adds 1 to the frequency count for v.
addValue(int) - Method in class org.apache.commons.math.stat.Frequency
  Adds 1 to the frequency count for v.
addValue(Integer) - Method in class org.apache.commons.math.stat.Frequency
  Adds 1 to the frequency count for v.
addValue(long) - Method in class org.apache.commons.math.stat.Frequency
  Adds 1 to the frequency count for v.
addValue(char) - Method in class org.apache.commons.math.stat.Frequency
  Adds 1 to the frequency count for v.
addValue(double) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Adds the value to the set of numbers
addValue(double) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatisticsImpl
addValue(double) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Adds the value to the data to be summarized
addValue(double) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
  Add a value to the data
apply(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Apply the given statistic to the data associated with this set of statistics.
apply(UnivariateStatistic) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatisticsImpl
  Apply the given statistic to this univariate collection.
asin(Complex) - Static method in class org.apache.commons.math.complex.ComplexUtils
  Compute the inverse sine for the given complex argument.
atan(Complex) - Static method in class org.apache.commons.math.complex.ComplexUtils
  Compute the inverse tangent for the given complex argument.

## B

Beta - class org.apache.commons.math.special.Beta.
  This is a utility class that provides computation methods related to the Beta family of functions.
BigMatrix - interface org.apache.commons.math.linear.BigMatrix.
  Interface defining a real-valued matrix with basic algebraic operations, using BigDecimal representations for the entries.
BigMatrixImpl - class org.apache.commons.math.linear.BigMatrixImpl.
  Implementation for `BigMatrix` using a BigDecimal[][] array to store entries and LU decompostion to support linear system solution and inverse.
BigMatrixImpl() - Constructor for class org.apache.commons.math.linear.BigMatrixImpl
  Creates a matrix with no data
BigMatrixImpl(int, int) - Constructor for class org.apache.commons.math.linear.BigMatrixImpl
  Create a new BigMatrix with the supplied row and column dimensions.
BigMatrixImpl(BigDecimal[][]) - Constructor for class org.apache.commons.math.linear.BigMatrixImpl
  Create a new BigMatrix using the `data` as the underlying data array.
BigMatrixImpl(double[][]) - Constructor for class org.apache.commons.math.linear.BigMatrixImpl
  Create a new BigMatrix using the `data` as the underlying data array.
BigMatrixImpl(String[][]) - Constructor for class org.apache.commons.math.linear.BigMatrixImpl
  Create a new BigMatrix using the values represented by the strings in `data` as the underlying data array.
BigMatrixImpl(BigDecimal[]) - Constructor for class org.apache.commons.math.linear.BigMatrixImpl
  Create a new (column) BigMatrix using `v` as the data for the unique column of the `v.length x 1` matrix created.
BinomialDistribution - interface org.apache.commons.math.distribution.BinomialDistribution.
  The Binomial Distribution.
BinomialDistributionImpl - class org.apache.commons.math.distribution.BinomialDistributionImpl.
  The default implementation of `BinomialDistribution`.
BinomialDistributionImpl(int, double) - Constructor for class org.apache.commons.math.distribution.BinomialDistributionImpl
  Create a binomial distribution with the given number of trials and probability of success.
BisectionSolver - class org.apache.commons.math.analysis.BisectionSolver.
  Implements the bisection algorithm for finding zeros of univariate real functions.
BisectionSolver(UnivariateRealFunction) - Constructor for class org.apache.commons.math.analysis.BisectionSolver
  Construct a solver for the given function.
BrentSolver - class org.apache.commons.math.analysis.BrentSolver.
  Implements the Brent algorithm for finding zeros of real univariate functions.
BrentSolver(UnivariateRealFunction) - Constructor for class org.apache.commons.math.analysis.BrentSolver
  Construct a solver for the given function.
binomialCoefficient(int, int) - Static method in class org.apache.commons.math.util.MathUtils
  Returns an exact representation of the Binomial Coefficient, "`n choose k`", the number of `k`-element subsets that can be selected from an `n`-element set.
binomialCoefficientDouble(int, int) - Static method in class org.apache.commons.math.util.MathUtils
  Returns a `double` representation of the Binomial Coefficient, "`n choose k`", the number of `k`-element subsets that can be selected from an `n`-element set.
binomialCoefficientLog(int, int) - Static method in class org.apache.commons.math.util.MathUtils
  Returns the natural `log` of the Binomial Coefficient, "`n choose k`", the number of `k`-element subsets that can be selected from an `n`-element set.
bracket(UnivariateRealFunction, double, double, double) - Static method in class org.apache.commons.math.analysis.UnivariateRealSolverUtils
  This method attempts to find two values a and b satisfying `lowerBound <= a < initial < b <= upperBound` `f(a) * f(b) < 0` If f is continuous on `[a,b],` this means that `a` and `b` bracket a root of f.
bracket(UnivariateRealFunction, double, double, double, int) - Static method in class org.apache.commons.math.analysis.UnivariateRealSolverUtils
  This method attempts to find two values a and b satisfying `lowerBound <= a < initial < b <= upperBound` `f(a) * f(b) < 0` If f is continuous on `[a,b],` this means that `a` and `b` bracket a root of f.

## C

CONSTANT_MODE - Static variable in class org.apache.commons.math.random.ValueServer
  Always return mu
ChiSquareTest - interface org.apache.commons.math.stat.inference.ChiSquareTest.
  An interface for Chi-Square tests.
ChiSquareTestImpl - class org.apache.commons.math.stat.inference.ChiSquareTestImpl.
  Implements Chi-Square test statistics defined in the `ChiSquareTest` interface.
ChiSquareTestImpl() - Constructor for class org.apache.commons.math.stat.inference.ChiSquareTestImpl
  Construct a ChiSquareTestImpl
ChiSquaredDistribution - interface org.apache.commons.math.distribution.ChiSquaredDistribution.
  The Chi-Squared Distribution.
ChiSquaredDistributionImpl - class org.apache.commons.math.distribution.ChiSquaredDistributionImpl.
  The default implementation of `ChiSquaredDistribution`
ChiSquaredDistributionImpl(double) - Constructor for class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Create a Chi-Squared distribution with the given degrees of freedom.
Complex - class org.apache.commons.math.complex.Complex.
  Representation of a Complex number - a number which has both a real and imaginary part.
Complex(double, double) - Constructor for class org.apache.commons.math.complex.Complex
  Create a complex number given the real and imaginary parts.
ComplexFormat - class org.apache.commons.math.complex.ComplexFormat.
  Formats a Complex number in cartesian format "Re(c) + Im(c)i".
ComplexFormat() - Constructor for class org.apache.commons.math.complex.ComplexFormat
  Create an instance with the default imaginary character, 'i', and the default number format for both real and imaginary parts.
ComplexFormat(NumberFormat) - Constructor for class org.apache.commons.math.complex.ComplexFormat
  Create an instance with a custom number format for both real and imaginary parts.
ComplexFormat(NumberFormat, NumberFormat) - Constructor for class org.apache.commons.math.complex.ComplexFormat
  Create an instance with a custom number format for the real part and a custom number format for the imaginary part.
ComplexFormat(String) - Constructor for class org.apache.commons.math.complex.ComplexFormat
  Create an instance with a custom imaginary character, and the default number format for both real and imaginary parts.
ComplexFormat(String, NumberFormat) - Constructor for class org.apache.commons.math.complex.ComplexFormat
  Create an instance with a custom imaginary character, and a custom number format for both real and imaginary parts.
ComplexFormat(String, NumberFormat, NumberFormat) - Constructor for class org.apache.commons.math.complex.ComplexFormat
  Create an instance with a custom imaginary character, a custom number format for the real part, and a custom number format for the imaginary part.
ComplexUtils - class org.apache.commons.math.complex.ComplexUtils.
  Implementations of various transcendental functions for `Complex` arguments.
ContinuedFraction - class org.apache.commons.math.util.ContinuedFraction.
  Provides a generic means to evaluate continued fractions.
ContinuedFraction() - Constructor for class org.apache.commons.math.util.ContinuedFraction
  Default constructor.
ContinuousDistribution - interface org.apache.commons.math.distribution.ContinuousDistribution.
  Base interface for continuous distributions.
ConvergenceException - exception org.apache.commons.math.ConvergenceException.
  Error thrown when a numerical computation can not be performed because the numerical result failed to converge to a finite value.
ConvergenceException() - Constructor for class org.apache.commons.math.ConvergenceException
  Default constructor.
ConvergenceException(String) - Constructor for class org.apache.commons.math.ConvergenceException
  Construct an exception with the given message.
ConvergenceException(String, Throwable) - Constructor for class org.apache.commons.math.ConvergenceException
  Construct an exception with the given message and root cause.
ConvergenceException(Throwable) - Constructor for class org.apache.commons.math.ConvergenceException
  Create an exception with a given root cause.
checkContractExpand(float, float) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Checks the expansion factor and the contraction criteria and throws an IllegalArgumentException if the contractionCriteria is less than the expansionCriteria
chiSquare(double[], long[]) - Method in interface org.apache.commons.math.stat.inference.ChiSquareTest
  Computes the Chi-Square statistic comparing `observed` and `expected` freqeuncy counts.
chiSquare(long[][]) - Method in interface org.apache.commons.math.stat.inference.ChiSquareTest
  Computes the Chi-Square statistic associated with a chi-square test of independence based on the input `counts` array, viewed as a two-way table.
chiSquare(double[], long[]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
chiSquare(long[][]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
chiSquareTest(double[], long[]) - Method in interface org.apache.commons.math.stat.inference.ChiSquareTest
  Returns the observed significance level, or p-value, associated with a Chi-square goodness of fit test comparing the `observed` frequency counts to those in the `expected` array.
chiSquareTest(double[], long[], double) - Method in interface org.apache.commons.math.stat.inference.ChiSquareTest
  Performs a Chi-square goodness of fit test evaluating the null hypothesis that the observed counts conform to the frequency distribution described by the expected counts, with significance level `alpha`.
chiSquareTest(long[][]) - Method in interface org.apache.commons.math.stat.inference.ChiSquareTest
  Returns the observed significance level, or p-value, associated with a chi-square test of independence based on the input `counts` array, viewed as a two-way table.
chiSquareTest(long[][], double) - Method in interface org.apache.commons.math.stat.inference.ChiSquareTest
  Performs a chi-square test of independence evaluating the null hypothesis that the classifications represented by the counts in the columns of the input 2-way table are independent of the rows, with significance level `alpha`.
chiSquareTest(double[], long[]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
chiSquareTest(double[], long[], double) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
chiSquareTest(long[][]) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
chiSquareTest(long[][], double) - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
classes() - Method in class org.apache.commons.math.util.TransformerMap
  Returns the Set of Classes used as keys in the map.
clear() - Method in class org.apache.commons.math.stat.Frequency
  Clears the frequency table
clear() - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
clear() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Resets all statistics and storage
clear() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatisticsImpl
clear() - Method in interface org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic
  Clears the internal state of the Statistic
clear() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Resets all statistics
clear() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
  Resets all statistics and storage
clear() - Method in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
clear() - Method in class org.apache.commons.math.stat.descriptive.moment.FourthMoment
clear() - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
clear() - Method in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
clear() - Method in class org.apache.commons.math.stat.descriptive.moment.Mean
clear() - Method in class org.apache.commons.math.stat.descriptive.moment.SecondMoment
clear() - Method in class org.apache.commons.math.stat.descriptive.moment.Skewness
clear() - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
clear() - Method in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
clear() - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
clear() - Method in class org.apache.commons.math.stat.descriptive.rank.Max
clear() - Method in class org.apache.commons.math.stat.descriptive.rank.Min
clear() - Method in class org.apache.commons.math.stat.descriptive.summary.Product
clear() - Method in class org.apache.commons.math.stat.descriptive.summary.Sum
clear() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
clear() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
clear() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Clears all data from the model.
clear() - Method in interface org.apache.commons.math.util.DoubleArray
  Clear the double array
clear() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Clear the array, reset the size to the initialCapacity and the number of elements to zero.
clear() - Method in class org.apache.commons.math.util.TransformerMap
  Clears all the Class to Transformer mappings.
clearResult() - Method in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Convenience function for implementations.
closeReplayFile() - Method in class org.apache.commons.math.random.ValueServer
  Closes `valuesFileURL` after use in REPLAY_MODE.
computeDistribution() - Method in class org.apache.commons.math.random.ValueServer
  Computes the empirical distribution using values from the file in `valuesFileURL`, using the default number of bins.
computeDistribution(int) - Method in class org.apache.commons.math.random.ValueServer
  Computes the empirical distribution using values from the file in `valuesFileURL` and `binCount` bins.
conjugate() - Method in class org.apache.commons.math.complex.Complex
  Return the conjugate of this complex number.
containsClass(Class) - Method in class org.apache.commons.math.util.TransformerMap
  Tests if a Class is present in the TransformerMap.
containsTransformer(NumberTransformer) - Method in class org.apache.commons.math.util.TransformerMap
  Tests if a NumberTransformer is present in the TransformerMap.
contract() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Contracts the storage array to the (size of the element set) + 1 - to avoid a zero length array.
contractionCriteria - Variable in class org.apache.commons.math.util.ResizableDoubleArray
  The contraction criteria determines when the internal array will be contracted to fit the number of elements contained in the element array + 1.
copy() - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Create a new BigMatrix which is a copy of this.
copy() - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns a (deep) copy of this.
copy() - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Create a new RealMatrix which is a copy of this.
cos(Complex) - Static method in class org.apache.commons.math.complex.ComplexUtils
  Compute the cosine for the given complex argument.
cosh(Complex) - Static method in class org.apache.commons.math.complex.ComplexUtils
  Compute the hyperbolic cosine for the given complex argument.
cosh(double) - Static method in class org.apache.commons.math.util.MathUtils
  Returns the hyperbolic cosine of x.
createBigMatrix(double[][]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Returns a `BigMatrix` whose entries are the the values in the the input array.
createBigMatrix(BigDecimal[][]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Returns a `BigMatrix` whose entries are the the values in the the input array.
createBigMatrix(String[][]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Returns a `BigMatrix` whose entries are the the values in the the input array.
createBinomialDistribution(int, double) - Method in class org.apache.commons.math.distribution.DistributionFactory
  Create a binomial distribution with the given number of trials and probability of success.
createBinomialDistribution(int, double) - Method in class org.apache.commons.math.distribution.DistributionFactoryImpl
  Create a binomial distribution with the given number of trials and probability of success.
createChiSquareDistribution(double) - Method in class org.apache.commons.math.distribution.DistributionFactory
  Create a new chi-square distribution with the given degrees of freedom.
createChiSquareDistribution(double) - Method in class org.apache.commons.math.distribution.DistributionFactoryImpl
  Create a new chi-square distribution with the given degrees of freedom.
createColumnBigMatrix(double[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Creates a column `BigMatrix` using the data from the input array.
createColumnBigMatrix(BigDecimal[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Creates a column `BigMatrix` using the data from the input array.
createColumnBigMatrix(String[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Creates a column `BigMatrix` using the data from the input array.
createColumnRealMatrix(double[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Creates a column `RealMatrix` using the data from the input array.
createExponentialDistribution(double) - Method in class org.apache.commons.math.distribution.DistributionFactory
  Create a new exponential distribution with the given degrees of freedom.
createExponentialDistribution(double) - Method in class org.apache.commons.math.distribution.DistributionFactoryImpl
  Create a new exponential distribution with the given degrees of freedom.
createFDistribution(double, double) - Method in class org.apache.commons.math.distribution.DistributionFactory
  Create a new F-distribution with the given degrees of freedom.
createFDistribution(double, double) - Method in class org.apache.commons.math.distribution.DistributionFactoryImpl
  Create a new F-distribution with the given degrees of freedom.
createGammaDistribution(double, double) - Method in class org.apache.commons.math.distribution.DistributionFactory
  Create a new gamma distribution with the given shape and scale parameters.
createGammaDistribution(double, double) - Method in class org.apache.commons.math.distribution.DistributionFactoryImpl
  Create a new gamma distribution the given shape and scale parameters.
createHypergeometricDistribution(int, int, int) - Method in class org.apache.commons.math.distribution.DistributionFactory
  Create a new hypergeometric distribution with the given the population size, the number of successes in the population, and the sample size.
createHypergeometricDistribution(int, int, int) - Method in class org.apache.commons.math.distribution.DistributionFactoryImpl
  Create a new hypergeometric distribution with the given the population size, the number of successes in the population, and the sample size.
createNormalDistribution(double, double) - Method in class org.apache.commons.math.distribution.DistributionFactory
  Create a new normal distribution with the given mean and standard deviation.
createNormalDistribution() - Method in class org.apache.commons.math.distribution.DistributionFactory
  Create a new normal distribution with mean zero and standard deviation one.
createNormalDistribution(double, double) - Method in class org.apache.commons.math.distribution.DistributionFactoryImpl
  Create a new normal distribution with the given mean and standard deviation.
createNormalDistribution() - Method in class org.apache.commons.math.distribution.DistributionFactoryImpl
  Create a new normal distribution with the mean zero and standard deviation one.
createPoissonDistribution(double) - Method in class org.apache.commons.math.distribution.DistributionFactory
  Create a new Poisson distribution with poisson parameter lambda.
createPoissonDistribution(double) - Method in class org.apache.commons.math.distribution.DistributionFactoryImpl
  Create a new Poisson distribution with poisson parameter lambda.
createRealMatrix(double[][]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Returns a `RealMatrix` whose entries are the the values in the the input array.
createRowBigMatrix(double[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Creates a row `BigMatrix` using the data from the input array.
createRowBigMatrix(BigDecimal[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Creates a row `BigMatrix` using the data from the input array.
createRowBigMatrix(String[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Creates a row `BigMatrix` using the data from the input array.
createRowRealMatrix(double[]) - Static method in class org.apache.commons.math.linear.MatrixUtils
  Creates a row `RealMatrix` using the data from the input array.
createTDistribution(double) - Method in class org.apache.commons.math.distribution.DistributionFactory
  Create a new t distribution with the given degrees of freedom.
createTDistribution(double) - Method in class org.apache.commons.math.distribution.DistributionFactoryImpl
  Create a new t distribution with the given degrees of freedom.
cumulativeProbability(double, double) - Method in class org.apache.commons.math.distribution.AbstractDistribution
  For a random variable X whose values are distributed according to this distribution, this method returns P(x0 ≤ X ≤ x1).
cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
  For a random variable X whose values are distributed according to this distribution, this method returns P(X ≤ x).
cumulativeProbability(int) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
  For a random variable X whose values are distributed according to this distribution, this method returns P(X ≤ x).
cumulativeProbability(int, int) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
  For a random variable X whose values are distributed according to this distribution, this method returns P(x0 ≤ X ≤ x1).
cumulativeProbability(int) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
  For this distribution, X, this method returns P(X ≤ x).
cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  For this disbution, X, this method returns P(X < x).
cumulativeProbability(double) - Method in interface org.apache.commons.math.distribution.Distribution
  For a random variable X whose values are distributed according to this distribution, this method returns P(X ≤ x).
cumulativeProbability(double, double) - Method in interface org.apache.commons.math.distribution.Distribution
  For a random variable X whose values are distributed according to this distribution, this method returns P(x0 ≤ X ≤ x1).
cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
  For this disbution, X, this method returns P(X < x).
cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
  For this disbution, X, this method returns P(X < x).
cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
  For this disbution, X, this method returns P(X < x).
cumulativeProbability(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  For this disbution, X, this method returns P(X ≤ x).
cumulativeProbability(int) - Method in interface org.apache.commons.math.distribution.IntegerDistribution
  For a random variable X whose values are distributed according to this distribution, this method returns P(X ≤ x).
cumulativeProbability(int, int) - Method in interface org.apache.commons.math.distribution.IntegerDistribution
  For this distribution, X, this method returns P(x0 ≤ X ≤ x1).
cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
  For this disbution, X, this method returns P(X < `x`).
cumulativeProbability(int) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
  The probability distribution function P(X <= x) for a Poisson distribution.
cumulativeProbability(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
  For this disbution, X, this method returns P(X < `x`).

## D

DIGEST_MODE - Static variable in class org.apache.commons.math.random.ValueServer
  Use empirical distribution
DefaultTransformer - class org.apache.commons.math.util.DefaultTransformer.
  A Default NumberTransformer for java.lang.Numbers and Numeric Strings.
DefaultTransformer() - Constructor for class org.apache.commons.math.util.DefaultTransformer
DescriptiveStatistics - class org.apache.commons.math.stat.descriptive.DescriptiveStatistics.
  Abstract factory class for univariate statistical summaries.
DescriptiveStatistics() - Constructor for class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
DescriptiveStatisticsImpl - class org.apache.commons.math.stat.descriptive.DescriptiveStatisticsImpl.
  Default implementation of `DescriptiveStatistics`.
DescriptiveStatisticsImpl() - Constructor for class org.apache.commons.math.stat.descriptive.DescriptiveStatisticsImpl
  Construct a DescriptiveStatisticsImpl with infinite window
DescriptiveStatisticsImpl(int) - Constructor for class org.apache.commons.math.stat.descriptive.DescriptiveStatisticsImpl
  Construct a DescriptiveStatisticsImpl with finite window
DifferentiableUnivariateRealFunction - interface org.apache.commons.math.analysis.DifferentiableUnivariateRealFunction.
  Extension of `UnivariateRealFunction` representing a differentiable univariate real function.
DiscreteDistribution - interface org.apache.commons.math.distribution.DiscreteDistribution.
  Base interface for discrete distributions.
Distribution - interface org.apache.commons.math.distribution.Distribution.
  Base interface for probability distributions.
DistributionFactory - class org.apache.commons.math.distribution.DistributionFactory.
  This factory provids the means to create common statistical distributions.
DistributionFactory() - Constructor for class org.apache.commons.math.distribution.DistributionFactory
  Default constructor.
DistributionFactoryImpl - class org.apache.commons.math.distribution.DistributionFactoryImpl.
  A concrete distribution factory.
DistributionFactoryImpl() - Constructor for class org.apache.commons.math.distribution.DistributionFactoryImpl
  Default constructor.
DoubleArray - interface org.apache.commons.math.util.DoubleArray.
  Provides a standard interface for double arrays.
defaultAbsoluteAccuracy - Variable in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Default maximum absolute error.
defaultFunctionValueAccuracy - Variable in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Default maximum error of function.
defaultMaximalIterationCount - Variable in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Default maximum number of iterations.
defaultRelativeAccuracy - Variable in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Default maximum relative error.
degree() - Method in class org.apache.commons.math.analysis.PolynomialFunction
  Returns the degree of the polynomial
derivative() - Method in interface org.apache.commons.math.analysis.DifferentiableUnivariateRealFunction
  Returns the derivative of the function
derivative() - Method in class org.apache.commons.math.analysis.PolynomialFunction
  Returns the derivative as a UnivariateRealFunction
derivative() - Method in class org.apache.commons.math.analysis.PolynomialSplineFunction
  Returns the derivative of the polynomial spline function as a UnivariateRealFunction
dev - Variable in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
  Deviation of most recently added value from previous first moment.
df(double, double, double, double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes approximate degrees of freedom for 2-sample t-test.
differentiate(double[]) - Static method in class org.apache.commons.math.analysis.PolynomialFunction
  Returns the coefficients of the derivative of the polynomial with the given coefficients.
discardFrontElements(int) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Discards the `i`initial elements of the array.``
divide(Complex) - Method in class org.apache.commons.math.complex.Complex
  Return the quotient of this complex number and the given complex number.

## E

EXPONENTIAL_MODE - Static variable in class org.apache.commons.math.random.ValueServer
  Exponential random deviates with mean = mu
EmpiricalDistribution - interface org.apache.commons.math.random.EmpiricalDistribution.
  Represents an empirical probability distribution -- a probability distribution derived from observed data without making any assumptions about the functional form of the population distribution that the data come from.
EmpiricalDistributionImpl - class org.apache.commons.math.random.EmpiricalDistributionImpl.
  Implements `EmpiricalDistribution` interface.
EmpiricalDistributionImpl() - Constructor for class org.apache.commons.math.random.EmpiricalDistributionImpl
  Creates a new EmpiricalDistribution with the default bin count.
EmpiricalDistributionImpl(int) - Constructor for class org.apache.commons.math.random.EmpiricalDistributionImpl
  Creates a new EmpiricalDistribution with the specified bin count.
Erf - class org.apache.commons.math.special.Erf.
  This is a utility class that provides computation methods related to the error functions.
ExponentialDistribution - interface org.apache.commons.math.distribution.ExponentialDistribution.
  The Exponential Distribution.
ExponentialDistributionImpl - class org.apache.commons.math.distribution.ExponentialDistributionImpl.
  The default implementation of `ExponentialDistribution`
ExponentialDistributionImpl(double) - Constructor for class org.apache.commons.math.distribution.ExponentialDistributionImpl
  Create a exponential distribution with the given mean.
eDA - Variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatisticsImpl
  Stored data values
equals(Object) - Method in class org.apache.commons.math.complex.Complex
  Test for the equality of two Complex objects.
equals(Object) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns true iff `object` is a `BigMatrixImpl` instance with the same dimensions as this and all corresponding matrix entries are equal.
equals(Object) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Returns true iff `object` is a `RealMatrixImpl` instance with the same dimensions as this and all corresponding matrix entries are equal.
equals(Object) - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
  Returns true iff `object` is an `AbstractStorelessUnivariateStatistic` returning the same values as this for `getResult()` and `getN()`
equals(Object) - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
  Returns true iff `object` is a `StatisticalSummaryValues` instance and all statistics have the same values as this.
equals(Object) - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns true iff `object` is a `SummaryStatistics` instance and all statistics have the same values as this.
equals(double, double) - Static method in class org.apache.commons.math.util.MathUtils
  Returns true iff both arguments are NaN or neither is NaN and they are equal
erf(double) - Static method in class org.apache.commons.math.special.Erf
  Returns the error function erf(x).
evaluate(double[], double) - Static method in class org.apache.commons.math.analysis.PolynomialFunction
  Uses Horner's Method to evaluate the polynomial with the given coefficients at the argument.
evaluate(double[]) - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
  This default implementation calls `AbstractStorelessUnivariateStatistic.clear()`, then invokes `AbstractStorelessUnivariateStatistic.increment(double)` in a loop over the the input array, and then uses `AbstractStorelessUnivariateStatistic.getResult()` to compute the return value.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
  This default implementation calls `AbstractStorelessUnivariateStatistic.clear()`, then invokes `AbstractStorelessUnivariateStatistic.increment(double)` in a loop over the specified portion of the input array, and then uses `AbstractStorelessUnivariateStatistic.getResult()` to compute the return value.
evaluate(double[]) - Method in class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
evaluate(double[]) - Method in interface org.apache.commons.math.stat.descriptive.UnivariateStatistic
  Returns the result of evaluating the statistic over the input array.
evaluate(double[], int, int) - Method in interface org.apache.commons.math.stat.descriptive.UnivariateStatistic
  Returns the result of evaluating the statistic over the specified entries in the input array.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
  Returns the geometric mean of the entries in the specified portion of the input array.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
  Returns the kurtosis of the entries in the specified portion of the input array.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.Mean
  Returns the arithmetic mean of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.Skewness
  Returns the Skewness of the entries in the specifed portion of the input array.
evaluate(double[]) - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Returns the Standard Deviation of the entries in the input array, or `Double.NaN` if the array is empty.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Returns the Standard Deviation of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
evaluate(double[], double, int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Returns the Standard Deviation of the entries in the specified portion of the input array, using the precomputed mean value.
evaluate(double[], double) - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Returns the Standard Deviation of the entries in the input array, using the precomputed mean value.
evaluate(double[]) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
  Returns the variance of the entries in the input array, or `Double.NaN` if the array is empty.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
  Returns the variance of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
evaluate(double[], double, int, int) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
  Returns the variance of the entries in the specified portion of the input array, using the precomputed mean value.
evaluate(double[], double) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
  Returns the variance of the entries in the input array, using the precomputed mean value.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.rank.Max
  Returns the maximum of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.rank.Min
  Returns the minimum of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
evaluate(double[], double) - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
  Returns an estimate of the `p`th percentile of the values in the `values` array.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
  Returns an estimate of the `quantile`th percentile of the designated values in the `values` array.
evaluate(double[], int, int, double) - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
  Returns an estimate of the `p`th percentile of the values in the `values` array, starting with the element in (0-based) position `begin` in the array and including `length` values.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.summary.Product
  Returns the product of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.summary.Sum
  The sum of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
  Returns the sum of the natural logs of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
evaluate(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
  Returns the sum of the squares of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
evaluate(double) - Method in class org.apache.commons.math.util.ContinuedFraction
  Evaluates the continued fraction at the value x.
evaluate(double, double) - Method in class org.apache.commons.math.util.ContinuedFraction
  Evaluates the continued fraction at the value x.
evaluate(double, int) - Method in class org.apache.commons.math.util.ContinuedFraction
  Evaluates the continued fraction at the value x.
evaluate(double, double, int) - Method in class org.apache.commons.math.util.ContinuedFraction
  Evaluates the continued fraction at the value x.
exp(Complex) - Static method in class org.apache.commons.math.complex.ComplexUtils
  Compute the exponential function for the given complex argument.
expand() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Expands the internal storage array using the expansion factor.
expansionFactor - Variable in class org.apache.commons.math.util.ResizableDoubleArray
  The expansion factor of the array.
expansionMode - Variable in class org.apache.commons.math.util.ResizableDoubleArray
  Determines whether array expansion by `expansionFactor` is additive or multiplicative.

## F

FDistribution - interface org.apache.commons.math.distribution.FDistribution.
  F-Distribution.
FDistributionImpl - class org.apache.commons.math.distribution.FDistributionImpl.
  Default implementation of `FDistribution`.
FDistributionImpl(double, double) - Constructor for class org.apache.commons.math.distribution.FDistributionImpl
  Create a F distribution using the given degrees of freedom.
FirstMoment - class org.apache.commons.math.stat.descriptive.moment.FirstMoment.
  Computes the first moment (arithmetic mean).
FirstMoment() - Constructor for class org.apache.commons.math.stat.descriptive.moment.FirstMoment
  Create a FirstMoment instance
FourthMoment - class org.apache.commons.math.stat.descriptive.moment.FourthMoment.
  Computes a statistic related to the Fourth Central Moment.
FourthMoment() - Constructor for class org.apache.commons.math.stat.descriptive.moment.FourthMoment
  Create a FourthMoment instance
Frequency - class org.apache.commons.math.stat.Frequency.
  Maintains a frequency distribution.
Frequency() - Constructor for class org.apache.commons.math.stat.Frequency
  Default constructor.
Frequency(Comparator) - Constructor for class org.apache.commons.math.stat.Frequency
  Constructor allowing values Comparator to be specified.
FunctionEvaluationException - exception org.apache.commons.math.FunctionEvaluationException.
  Exeption thrown when an error occurs evaluating a function.
FunctionEvaluationException(double) - Constructor for class org.apache.commons.math.FunctionEvaluationException
  Construct an exception indicating the argument value that caused the function evaluation to fail.
FunctionEvaluationException(double, String) - Constructor for class org.apache.commons.math.FunctionEvaluationException
  Construct an exception using the given argument and message text.
FunctionEvaluationException(double, String, Throwable) - Constructor for class org.apache.commons.math.FunctionEvaluationException
  Construct an exception with the given argument, message and root cause.
f - Variable in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  The function to solve.
factorial(int) - Static method in class org.apache.commons.math.util.MathUtils
  Returns n!.
factorialDouble(int) - Static method in class org.apache.commons.math.util.MathUtils
  Returns n!.
factorialLog(int) - Static method in class org.apache.commons.math.util.MathUtils
  Returns the natural logarithm of n!.
fill(double[]) - Method in class org.apache.commons.math.random.ValueServer
  Fills the input array with values generated using getNext() repeatedly.
fill(int) - Method in class org.apache.commons.math.random.ValueServer
  Returns an array of length `length` with values generated using getNext() repeatedly.
format(Complex, StringBuffer, FieldPosition) - Method in class org.apache.commons.math.complex.ComplexFormat
  Formats a `Complex` object to produce a string.
format(Object, StringBuffer, FieldPosition) - Method in class org.apache.commons.math.complex.ComplexFormat
  Formats a object to produce a string.
formatComplex(Complex) - Static method in class org.apache.commons.math.complex.ComplexFormat
  This static method calls formatComplex() on a default instance of ComplexFormat.
functionValueAccuracy - Variable in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Maximum error of function.

## G

GAUSSIAN_MODE - Static variable in class org.apache.commons.math.random.ValueServer
  Gaussian random deviates with mean = mu, std dev = sigma
Gamma - class org.apache.commons.math.special.Gamma.
  This is a utility class that provides computation methods related to the Gamma family of functions.
GammaDistribution - interface org.apache.commons.math.distribution.GammaDistribution.
  The Gamma Distribution.
GammaDistributionImpl - class org.apache.commons.math.distribution.GammaDistributionImpl.
  The default implementation of `GammaDistribution`
GammaDistributionImpl(double, double) - Constructor for class org.apache.commons.math.distribution.GammaDistributionImpl
  Create a new gamma distribution with the given alpha and beta values.
GeometricMean - class org.apache.commons.math.stat.descriptive.moment.GeometricMean.
  Returns the geometric mean of the available values.
GeometricMean() - Constructor for class org.apache.commons.math.stat.descriptive.moment.GeometricMean
  Create a GeometricMean instance
geoMean - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
  geoMean of values that have been added
geometricMean(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the geometric mean of the entries in the input array, or `Double.NaN` if the array is empty.
geometricMean(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the geometric mean of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
getA(int, double) - Method in class org.apache.commons.math.util.ContinuedFraction
  Access the n-th a coefficient of the continued fraction.
getAbsoluteAccuracy() - Method in interface org.apache.commons.math.analysis.UnivariateRealSolver
  Get the actual absolute accuracy.
getAbsoluteAccuracy() - Method in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Get the actual absolute accuracy.
getAlpha() - Method in interface org.apache.commons.math.distribution.GammaDistribution
  Access the shape parameter, alpha
getAlpha() - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
  Access the shape parameter, alpha
getArgument() - Method in class org.apache.commons.math.FunctionEvaluationException
  Returns the function argument that caused this exception.
getAvailableLocales() - Static method in class org.apache.commons.math.complex.ComplexFormat
  Get the set of locales for which complex formats are available.
getB(int, double) - Method in class org.apache.commons.math.util.ContinuedFraction
  Access the n-th b coefficient of the continued fraction.
getBeta() - Method in interface org.apache.commons.math.distribution.GammaDistribution
  Access the scale parameter, beta
getBeta() - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
  Access the scale parameter, beta
getBinCount() - Method in interface org.apache.commons.math.random.EmpiricalDistribution
  Returns the number of bins.
getBinCount() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Returns the number of bins.
getBinStats() - Method in interface org.apache.commons.math.random.EmpiricalDistribution
  Returns a list of `SummaryStatistics` containing statistics describing the values in each of the bins.
getBinStats() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Returns an ArrayList of `SummaryStatistics` instances containing statistics describing the values in each of the bins.
getCause() - Method in class org.apache.commons.math.MathException
  Gets the cause of this throwable.
getCoefficients() - Method in class org.apache.commons.math.analysis.PolynomialFunction
  Returns a copy of the coefficients array.
getColumn(int) - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns the entries in column number `col` as an array.
getColumn(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns the entries in column number `col` as an array.
getColumn(int) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the entries in column number `col` as an array.
getColumn(int) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Returns the entries in column number `col` as an array.
getColumnAsDoubleArray(int) - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns the entries in column number `col` as an array of double values.
getColumnAsDoubleArray(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns the entries in column number `col` as an array of double values.
getColumnDimension() - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns the number of columns in the matrix.
getColumnDimension() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns the number of columns in the matrix.
getColumnDimension() - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the number of columns in the matrix.
getColumnDimension() - Method in class org.apache.commons.math.linear.RealMatrixImpl
getColumnMatrix(int) - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns the entries in column number `column` as a column matrix.
getColumnMatrix(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns the entries in column number `column` as a column matrix.
getColumnMatrix(int) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the entries in column number `column` as a column matrix.
getColumnMatrix(int) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Returns the entries in column number `column` as a column matrix.
getContractionCriteria() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  The contraction criteria defines when the internal array will contract to store only the number of elements in the element array.
getCount(Object) - Method in class org.apache.commons.math.stat.Frequency
  Returns the number of values = v.
getCount(int) - Method in class org.apache.commons.math.stat.Frequency
  Returns the number of values = v.
getCount(long) - Method in class org.apache.commons.math.stat.Frequency
  Returns the number of values = v.
getCount(char) - Method in class org.apache.commons.math.stat.Frequency
  Returns the number of values = v.
getCumFreq(Object) - Method in class org.apache.commons.math.stat.Frequency
  Returns the cumulative frequency of values less than or equal to v.
getCumFreq(int) - Method in class org.apache.commons.math.stat.Frequency
  Returns the cumulative frequency of values less than or equal to v.
getCumFreq(long) - Method in class org.apache.commons.math.stat.Frequency
  Returns the cumulative frequency of values less than or equal to v.
getCumFreq(char) - Method in class org.apache.commons.math.stat.Frequency
  Returns the cumulative frequency of values less than or equal to v.
getCumPct(Object) - Method in class org.apache.commons.math.stat.Frequency
  Returns the cumulative percentage of values less than or equal to v (as a proportion between 0 and 1).
getCumPct(int) - Method in class org.apache.commons.math.stat.Frequency
  Returns the cumulative percentage of values less than or equal to v (as a proportion between 0 and 1).
getCumPct(long) - Method in class org.apache.commons.math.stat.Frequency
  Returns the cumulative percentage of values less than or equal to v (as a proportion between 0 and 1).
getCumPct(char) - Method in class org.apache.commons.math.stat.Frequency
  Returns the cumulative percentage of values less than or equal to v (as a proportion between 0 and 1).
getData() - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns matrix entries as a two-dimensional array.
getData() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns matrix entries as a two-dimensional array.
getData() - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns matrix entries as a two-dimensional array.
getData() - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Returns matrix entries as a two-dimensional array.
getDataAsDoubleArray() - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns matrix entries as a two-dimensional array.
getDataAsDoubleArray() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns matrix entries as a two-dimensional array.
getDataRef() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns a reference to the underlying data array.
getDataRef() - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Returns a reference to the underlying data array.
getDegreesOfFreedom() - Method in interface org.apache.commons.math.distribution.ChiSquaredDistribution
  Access the degrees of freedom.
getDegreesOfFreedom() - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Access the degrees of freedom.
getDegreesOfFreedom() - Method in interface org.apache.commons.math.distribution.TDistribution
  Access the degrees of freedom.
getDegreesOfFreedom() - Method in class org.apache.commons.math.distribution.TDistributionImpl
  Access the degrees of freedom.
getDenominatorDegreesOfFreedom() - Method in interface org.apache.commons.math.distribution.FDistribution
  Access the denominator degrees of freedom.
getDenominatorDegreesOfFreedom() - Method in class org.apache.commons.math.distribution.FDistributionImpl
  Access the denominator degrees of freedom.
getDeterminant() - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns the determinant of this matrix.
getDeterminant() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns the determinant of this matrix.
getDeterminant() - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the determinant of this matrix.
getDeterminant() - Method in class org.apache.commons.math.linear.RealMatrixImpl
getDistributionFactory() - Method in class org.apache.commons.math.stat.inference.ChiSquareTestImpl
  Gets a DistributionFactory to use in creating ChiSquaredDistribution instances.
getDistributionFactory() - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Gets a DistributionFactory to use in creating TDistribution instances.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.AbstractContinuousDistribution
  Access the domain value lower bound, based on `p`, used to bracket a CDF root.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
  Access the domain value lower bound, based on `p`, used to bracket a PDF root.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
  Access the domain value lower bound, based on `p`, used to bracket a PDF root.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Access the domain value lower bound, based on `p`, used to bracket a CDF root.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
  Access the domain value lower bound, based on `p`, used to bracket a CDF root.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
  Access the domain value lower bound, based on `p`, used to bracket a CDF root.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
  Access the domain value lower bound, based on `p`, used to bracket a CDF root.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Access the domain value lower bound, based on `p`, used to bracket a PDF root.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
  Access the domain value lower bound, based on `p`, used to bracket a CDF root.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
  Access the domain value lower bound, based on `p`, used to bracket a CDF root.
getDomainLowerBound(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
  Access the domain value lower bound, based on `p`, used to bracket a CDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.AbstractContinuousDistribution
  Access the domain value upper bound, based on `p`, used to bracket a CDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
  Access the domain value upper bound, based on `p`, used to bracket a PDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
  Access the domain value upper bound, based on `p`, used to bracket a PDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Access the domain value upper bound, based on `p`, used to bracket a CDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
  Access the domain value upper bound, based on `p`, used to bracket a CDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
  Access the domain value upper bound, based on `p`, used to bracket a CDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
  Access the domain value upper bound, based on `p`, used to bracket a CDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Access the domain value upper bound, based on `p`, used to bracket a PDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
  Access the domain value upper bound, based on `p`, used to bracket a CDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
  Access the domain value upper bound, based on `p`, used to bracket a CDF root.
getDomainUpperBound(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
  Access the domain value upper bound, based on `p`, used to bracket a CDF root.
getElement(int) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the element at the specified index
getElement(int) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatisticsImpl
getElement(int) - Method in interface org.apache.commons.math.util.DoubleArray
  Returns the element at the specified index.
getElement(int) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Returns the element at the specified index
getElements() - Method in interface org.apache.commons.math.util.DoubleArray
  Returns a double[] array containing the elements of this `DoubleArray`.
getElements() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Returns a double array containing the elements of this `ResizableArray`.
getEmpiricalDistribution() - Method in class org.apache.commons.math.random.ValueServer
  Getter for property empiricalDistribution.
getEntry(int, int) - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns the entry in the specified row and column.
getEntry(int, int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns the entry in the specified row and column.
getEntry(int, int) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the entry in the specified row and column.
getEntry(int, int) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Returns the entry in the specified row and column.
getEntryAsDouble(int, int) - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns the entry in the specified row and column as a double.
getEntryAsDouble(int, int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns the entry in the specified row and column as a double.
getExpansionFactor() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  The expansion factor controls the size of a new aray when an array needs to be expanded.
getExpansionMode() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  The `expansionMode` determines whether the internal storage array grows additively (ADDITIVE_MODE) or multiplicatively (MULTIPLICATIVE_MODE) when it is expanded.
getFunctionValueAccuracy() - Method in interface org.apache.commons.math.analysis.UnivariateRealSolver
  Get the actual function value accuracy.
getFunctionValueAccuracy() - Method in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Get the actual function value accuracy.
getGeometricMean() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the geometric mean of the available values
getGeometricMean() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the geometric mean of the available values
getGeometricMean() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
  Returns the geometric mean of the values that have been added.
getIdentity(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns `dimension x dimension` identity matrix.
getIdentity(int) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Returns `dimension x dimension` identity matrix.
getImaginary() - Method in class org.apache.commons.math.complex.Complex
  Access the imaginary part.
getImaginaryCharacter() - Method in class org.apache.commons.math.complex.ComplexFormat
  Access the imaginaryCharacter.
getImaginaryFormat() - Method in class org.apache.commons.math.complex.ComplexFormat
  Access the imaginaryFormat.
getInitialDomain(double) - Method in class org.apache.commons.math.distribution.AbstractContinuousDistribution
  Access the initial domain value, based on `p`, used to bracket a CDF root.
getInitialDomain(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Access the initial domain value, based on `p`, used to bracket a CDF root.
getInitialDomain(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
  Access the initial domain value, based on `p`, used to bracket a CDF root.
getInitialDomain(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
  Access the initial domain value, based on `p`, used to bracket a CDF root.
getInitialDomain(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
  Access the initial domain value, based on `p`, used to bracket a CDF root.
getInitialDomain(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
  Access the initial domain value, based on `p`, used to bracket a CDF root.
getInitialDomain(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
  Access the initial domain value, based on `p`, used to bracket a CDF root.
getInstance() - Static method in class org.apache.commons.math.complex.ComplexFormat
  Returns the default complex format for the current locale.
getInstance(Locale) - Static method in class org.apache.commons.math.complex.ComplexFormat
  Returns the default complex format for the given locale.
getIntercept() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the intercept of the estimated regression line.
getInterceptStdErr() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the standard error of the intercept estimate, usually denoted s(b0).
getInternalLength() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Notice the package scope on this method.
getIterationCount() - Method in interface org.apache.commons.math.analysis.UnivariateRealSolver
  Get the number of iterations in the last run of the solver.
getIterationCount() - Method in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Access the last iteration count.
getKnots() - Method in class org.apache.commons.math.analysis.PolynomialSplineFunction
  Returns an array copy of the knot points.
getKurtosis() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the Kurtosis of the available values.
getLUMatrix() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns the LU decomposition as a BigMatrix.
getLUMatrix() - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Returns the LU decomposition as a RealMatrix.
getMax() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the maximum of the available values
getMax() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
  Returns the maximum of the available values
getMax() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
getMax() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the maximum of the available values
getMax() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
  Returns the maximum of the values that have been added.
getMaximalIterationCount() - Method in interface org.apache.commons.math.analysis.UnivariateRealSolver
  Get the upper limit for the number of iterations.
getMaximalIterationCount() - Method in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Get the upper limit for the number of iterations.
getMean() - Method in interface org.apache.commons.math.distribution.ExponentialDistribution
  Access the mean.
getMean() - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
  Access the mean.
getMean() - Method in interface org.apache.commons.math.distribution.NormalDistribution
  Access the mean.
getMean() - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
  Access the mean.
getMean() - Method in interface org.apache.commons.math.distribution.PoissonDistribution
  Get the mean for the distribution.
getMean() - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
  Get the Poisson mean for the distribution.
getMean() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the arithmetic mean of the available values
getMean() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
  Returns the arithmetic mean of the available values
getMean() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
getMean() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the arithmetic mean of the available values
getMean() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
  Returns the mean of the values that have been added.
getMeanSquareError() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the sum of squared errors divided by the degrees of freedom, usually abbreviated MSE.
getMin() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the minimum of the available values
getMin() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
  Returns the minimum of the available values
getMin() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
getMin() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the minimum of the available values
getMin() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
  Returns the minimum of the values that have been added.
getMode() - Method in class org.apache.commons.math.random.ValueServer
  Getter for property mode.
getMu() - Method in class org.apache.commons.math.random.ValueServer
  Getter for property mu.
getN() - Method in class org.apache.commons.math.analysis.PolynomialSplineFunction
  Returns the number of spline segments = the number of polynomials = the number of knot points - 1.
getN() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the number of available values
getN() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatisticsImpl
getN() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
  Returns the number of available values
getN() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
getN() - Method in interface org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic
  Returns the number of values that have been added.
getN() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the number of available values
getN() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
  Returns the number of available values
getN() - Method in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
getN() - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
getN() - Method in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
getN() - Method in class org.apache.commons.math.stat.descriptive.moment.Mean
getN() - Method in class org.apache.commons.math.stat.descriptive.moment.Skewness
getN() - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
getN() - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
getN() - Method in class org.apache.commons.math.stat.descriptive.rank.Max
getN() - Method in class org.apache.commons.math.stat.descriptive.rank.Min
getN() - Method in class org.apache.commons.math.stat.descriptive.summary.Product
getN() - Method in class org.apache.commons.math.stat.descriptive.summary.Sum
getN() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
getN() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
getN() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the number of observations that have been added to the model.
getNext() - Method in class org.apache.commons.math.random.ValueServer
  Returns the next generated value, generated according to the mode value (see MODE constants).
getNextValue() - Method in interface org.apache.commons.math.random.EmpiricalDistribution
  Generates a random value from this distribution.
getNextValue() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Generates a random value from this distribution.
getNorm() - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns the maximum absolute row sum norm of the matrix.
getNorm() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns the maximum absolute row sum norm of the matrix.
getNorm() - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the maximum absolute row sum norm of the matrix.
getNorm() - Method in class org.apache.commons.math.linear.RealMatrixImpl
getNumElements() - Method in interface org.apache.commons.math.util.DoubleArray
  Returns the number of elements currently in the array.
getNumElements() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Returns the number of elements currently in the array.
getNumberOfSuccesses() - Method in interface org.apache.commons.math.distribution.HypergeometricDistribution
  Access the number of successes.
getNumberOfSuccesses() - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Access the number of successes.
getNumberOfTrials() - Method in interface org.apache.commons.math.distribution.BinomialDistribution
  Access the number of trials for this distribution.
getNumberOfTrials() - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
  Access the number of trials for this distribution.
getNumeratorDegreesOfFreedom() - Method in interface org.apache.commons.math.distribution.FDistribution
  Access the numerator degrees of freedom.
getNumeratorDegreesOfFreedom() - Method in class org.apache.commons.math.distribution.FDistributionImpl
  Access the numerator degrees of freedom.
getPct(Object) - Method in class org.apache.commons.math.stat.Frequency
  Returns the percentage of values that are equal to v (as a proportion between 0 and 1).
getPct(int) - Method in class org.apache.commons.math.stat.Frequency
  Returns the percentage of values that are equal to v (as a proportion between 0 and 1).
getPct(long) - Method in class org.apache.commons.math.stat.Frequency
  Returns the percentage of values that are equal to v (as a proportion between 0 and 1).
getPct(char) - Method in class org.apache.commons.math.stat.Frequency
  Returns the percentage of values that are equal to v (as a proportion between 0 and 1).
getPercentile(double) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns an estimate for the pth percentile of the stored values.
getPermutation() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns the permutation associated with the lu decomposition.
getPermutation() - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Returns the permutation associated with the lu decomposition.
getPolynomials() - Method in class org.apache.commons.math.analysis.PolynomialSplineFunction
  Returns a copy of the interpolating polynomials array.
getPopulationSize() - Method in interface org.apache.commons.math.distribution.HypergeometricDistribution
  Access the population size.
getPopulationSize() - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Access the population size.
getProbabilityOfSuccess() - Method in interface org.apache.commons.math.distribution.BinomialDistribution
  Access the probability of success for this distribution.
getProbabilityOfSuccess() - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
  Access the probability of success for this distribution.
getQuantile() - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
  Returns the value of the quantile field (determines what percentile is computed when evaluate() is called with no quantile argument).
getR() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns Pearson's product moment correlation coefficient, usually denoted r.
getRSquare() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the coefficient of determination, usually denoted r-square.
getReal() - Method in class org.apache.commons.math.complex.Complex
  Access the real part.
getRealFormat() - Method in class org.apache.commons.math.complex.ComplexFormat
  Access the realFormat.
getRegressionSumSquares() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the sum of squared deviations of the predicted y values about their mean (which equals the mean of y).
getRelativeAccuracy() - Method in interface org.apache.commons.math.analysis.UnivariateRealSolver
  Get the actual relative accuracy.
getRelativeAccuracy() - Method in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Get the actual relative accuracy.
getResult() - Method in interface org.apache.commons.math.analysis.UnivariateRealSolver
  Get the result of the last run of the solver.
getResult() - Method in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Access the last computed root.
getResult() - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
getResult() - Method in interface org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic
  Returns the current value of the Statistic.
getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.FourthMoment
getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.Mean
getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.SecondMoment
getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.Skewness
  Returns the value of the statistic based on the values that have been added.
getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
getResult() - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
getResult() - Method in class org.apache.commons.math.stat.descriptive.rank.Max
getResult() - Method in class org.apache.commons.math.stat.descriptive.rank.Min
getResult() - Method in class org.apache.commons.math.stat.descriptive.summary.Product
getResult() - Method in class org.apache.commons.math.stat.descriptive.summary.Sum
getResult() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
getResult() - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
getRoundingMode() - Method in interface org.apache.commons.math.linear.BigMatrix
  Gets the rounding mode
getRoundingMode() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Gets the rounding mode for division operations The default is `BigDecimal.ROUND_HALF_UP`
getRow(int) - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns the entries in row number `row` as an array.
getRow(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns the entries in row number `row` as an array.
getRow(int) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the entries in row number `row` as an array.
getRow(int) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Returns the entries in row number `row` as an array.
getRowAsDoubleArray(int) - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns the entries in row number `row` as an array of double values.
getRowAsDoubleArray(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns the entries in row number `row` as an array of double values.
getRowDimension() - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns the number of rows in the matrix.
getRowDimension() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns the number of rows in the matrix.
getRowDimension() - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the number of rows in the matrix.
getRowDimension() - Method in class org.apache.commons.math.linear.RealMatrixImpl
getRowMatrix(int) - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns the entries in row number `row` as a row matrix.
getRowMatrix(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns the entries in row number `row` as a row matrix.
getRowMatrix(int) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the entries in row number `row` as a row matrix.
getRowMatrix(int) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Returns the entries in row number `row` as a row matrix.
getSampleSize() - Method in interface org.apache.commons.math.distribution.HypergeometricDistribution
  Access the sample size.
getSampleSize() - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Access the sample size.
getSampleStats() - Method in interface org.apache.commons.math.random.EmpiricalDistribution
  Returns a `StatisticalSummary` describing this distribution.
getSampleStats() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Returns a `StatisticalSummary` describing this distribution.
getScale() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Sets the scale for division operations.
getSigma() - Method in class org.apache.commons.math.random.ValueServer
  Getter for property sigma.
getSignificance() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the significance level of the slope (equiv) correlation.
getSkewness() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the skewness of the available values.
getSlope() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the slope of the estimated regression line.
getSlopeConfidenceInterval() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the half-width of a 95% confidence interval for the slope estimate.
getSlopeConfidenceInterval(double) - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the half-width of a (100-100*alpha)% confidence interval for the slope estimate.
getSlopeStdErr() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the standard error of the slope estimate, usually denoted s(b1).
getSortedValues() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the current set of values in an array of double primitives, sorted in ascending order.
getStandardDeviation() - Method in interface org.apache.commons.math.distribution.NormalDistribution
  Access the standard deviation.
getStandardDeviation() - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
  Access the standard deviation.
getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the standard deviation of the available values.
getStandardDeviation() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
  Returns the standard deviation of the available values.
getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the standard deviation of the available values.
getStandardDeviation() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
  Returns the standard deviation of the values that have been added.
getSubMatrix(int, int, int, int) - Method in interface org.apache.commons.math.linear.BigMatrix
  Gets a submatrix.
getSubMatrix(int[], int[]) - Method in interface org.apache.commons.math.linear.BigMatrix
  Gets a submatrix.
getSubMatrix(int, int, int, int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Gets a submatrix.
getSubMatrix(int[], int[]) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Gets a submatrix.
getSubMatrix(int, int, int, int) - Method in interface org.apache.commons.math.linear.RealMatrix
  Gets a submatrix.
getSubMatrix(int[], int[]) - Method in interface org.apache.commons.math.linear.RealMatrix
  Gets a submatrix.
getSubMatrix(int, int, int, int) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Gets a submatrix.
getSubMatrix(int[], int[]) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Gets a submatrix.
getSum() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the sum of the values that have been added to Univariate.
getSum() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
  Returns the sum of the values that have been added to Univariate.
getSum() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
getSum() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the sum of the values that have been added to Univariate.
getSum() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
  Returns the sum of the values that have been added to Univariate.
getSumFreq() - Method in class org.apache.commons.math.stat.Frequency
  Returns the sum of all frequencies.
getSumSquaredErrors() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the sum of squared errors (SSE) associated with the regression model.
getSummary() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Return a `StatisticalSummaryValues` instance reporting current statistics.
getSumsq() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the sum of the squares of the available values.
getSumsq() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the sum of the squares of the available values.
getSumsq() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
  Returns the sum of the squares of the values that have been added.
getTotalSumSquares() - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the sum of squared deviations of the y values about their mean.
getTrace() - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns the trace of the matrix (the sum of the elements on the main diagonal).
getTrace() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns the trace of the matrix (the sum of the elements on the main diagonal).
getTrace() - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the trace of the matrix (the sum of the elements on the main diagonal).
getTrace() - Method in class org.apache.commons.math.linear.RealMatrixImpl
getTransformer(Class) - Method in class org.apache.commons.math.util.TransformerMap
  Returns the Transformer that is mapped to a class if mapping is not present, this returns null.
getUpperBounds() - Method in interface org.apache.commons.math.random.EmpiricalDistribution
  Returns the array of upper bounds for the bins.
getUpperBounds() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Returns the array of upper bounds for the bins.
getValues() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the current set of values in an array of double primitives.
getValues() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatisticsImpl
getValues() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Returns the internal storage array.
getValuesFileURL() - Method in class org.apache.commons.math.random.ValueServer
  Getter for `valuesFileURL```
getVariance() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Returns the variance of the available values.
getVariance() - Method in interface org.apache.commons.math.stat.descriptive.StatisticalSummary
  Returns the variance of the available values.
getVariance() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
getVariance() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns the variance of the available values.
getVariance() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
  Returns the variance of the values that have been added.
getWindowSize() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Univariate has the ability to return only measures for the last N elements added to the set of values.
getWindowSize() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatisticsImpl
  Access the window size.

## H

HypergeometricDistribution - interface org.apache.commons.math.distribution.HypergeometricDistribution.
  The Hypergeometric Distribution.
HypergeometricDistributionImpl - class org.apache.commons.math.distribution.HypergeometricDistributionImpl.
  The default implementation of `HypergeometricDistribution`.
HypergeometricDistributionImpl(int, int, int) - Constructor for class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Construct a new hypergeometric distribution with the given the population size, the number of successes in the population, and the sample size.
hash(double) - Static method in class org.apache.commons.math.util.MathUtils
  Returns an integer hash code representing the given double value.
hashCode() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Computes a hashcode for the matrix.
hashCode() - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Computes a hashcode for the matrix.
hashCode() - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
  Returns hash code based on getResult() and getN()
hashCode() - Method in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
  Returns hash code based on values of statistics
hashCode() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Returns hash code based on values of statistics
homoscedasticT(double[], double[]) - Method in interface org.apache.commons.math.stat.inference.TTest
  Computes a 2-sample t statistic, under the hypothesis of equal subpopulation variances.
homoscedasticT(StatisticalSummary, StatisticalSummary) - Method in interface org.apache.commons.math.stat.inference.TTest
  Computes a 2-sample t statistic, comparing the means of the datasets described by two `StatisticalSummary` instances, under the assumption of equal subpopulation variances.
homoscedasticT(double[], double[]) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes a 2-sample t statistic, under the hypothesis of equal subpopulation variances.
homoscedasticT(StatisticalSummary, StatisticalSummary) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes a 2-sample t statistic, comparing the means of the datasets described by two `StatisticalSummary` instances, under the assumption of equal subpopulation variances.
homoscedasticT(double, double, double, double, double, double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes t test statistic for 2-sample t-test under the hypothesis of equal subpopulation variances.
homoscedasticTTest(double[], double[]) - Method in interface org.apache.commons.math.stat.inference.TTest
  Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays, under the assumption that the two samples are drawn from subpopulations with equal variances.
homoscedasticTTest(double[], double[], double) - Method in interface org.apache.commons.math.stat.inference.TTest
  Performs a two-sided t-test evaluating the null hypothesis that `sample1` and `sample2` are drawn from populations with the same mean, with significance level `alpha`, assuming that the subpopulation variances are equal.
homoscedasticTTest(StatisticalSummary, StatisticalSummary) - Method in interface org.apache.commons.math.stat.inference.TTest
  Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances, under the hypothesis of equal subpopulation variances.
homoscedasticTTest(double[], double[]) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays, under the assumption that the two samples are drawn from subpopulations with equal variances.
homoscedasticTTest(double[], double[], double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Performs a two-sided t-test evaluating the null hypothesis that `sample1` and `sample2` are drawn from populations with the same mean, with significance level `alpha`, assuming that the subpopulation variances are equal.
homoscedasticTTest(StatisticalSummary, StatisticalSummary) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances, under the hypothesis of equal subpopulation variances.
homoscedasticTTest(double, double, double, double, double, double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes p-value for 2-sided, 2-sample t-test, under the assumption of equal subpopulation variances.

## I

I - Static variable in class org.apache.commons.math.complex.Complex
  The square root of -1.
INFINITE_WINDOW - Static variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  This constant signals that a Univariate implementation takes into account the contributions of an infinite number of elements.
IntegerDistribution - interface org.apache.commons.math.distribution.IntegerDistribution.
  Interface for discrete distributions of integer-valued random variables.
InvalidMatrixException - exception org.apache.commons.math.linear.InvalidMatrixException.
  Thrown when a system attempts an operation on a matrix, and that matrix does not satisfy the preconditions for the aforementioned operation.
InvalidMatrixException() - Constructor for class org.apache.commons.math.linear.InvalidMatrixException
  Default constructor.
InvalidMatrixException(String) - Constructor for class org.apache.commons.math.linear.InvalidMatrixException
  Construct an exception with the given message.
imaginary - Variable in class org.apache.commons.math.complex.Complex
  The imaginary part.
incMoment - Variable in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
  Determines whether or not this statistic can be incremented or cleared.
incMoment - Variable in class org.apache.commons.math.stat.descriptive.moment.Mean
  Determines whether or not this statistic can be incremented or cleared.
incMoment - Variable in class org.apache.commons.math.stat.descriptive.moment.Skewness
  Determines whether or not this statistic can be incremented or cleared.
incMoment - Variable in class org.apache.commons.math.stat.descriptive.moment.Variance
  Boolean test to determine if this Variance should also increment the second moment, this evaluates to false when this Variance is constructed with an external SecondMoment as a parameter.
increment(double) - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
increment(double) - Method in interface org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic
  Updates the internal state of the statistic to reflect the addition of the new value.
increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.FourthMoment
increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.Mean
increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.SecondMoment
increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.Skewness
increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
increment(double) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
increment(double) - Method in class org.apache.commons.math.stat.descriptive.rank.Max
increment(double) - Method in class org.apache.commons.math.stat.descriptive.rank.Min
increment(double) - Method in class org.apache.commons.math.stat.descriptive.summary.Product
increment(double) - Method in class org.apache.commons.math.stat.descriptive.summary.Sum
increment(double) - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
increment(double) - Method in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
incrementAll(double[]) - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
  This default implementation just calls `AbstractStorelessUnivariateStatistic.increment(double)` in a loop over the input array.
incrementAll(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
  This default implementation just calls `AbstractStorelessUnivariateStatistic.increment(double)` in a loop over the specified portion of the input array.
incrementAll(double[]) - Method in interface org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic
  Updates the internal state of the statistic to reflect addition of all values in the values array.
incrementAll(double[], int, int) - Method in interface org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic
  Updates the internal state of the statistic to reflect addition of the values in the designated portion of the values array.
indicator(double) - Static method in class org.apache.commons.math.util.MathUtils
  For a double precision value x, this method returns +1.0 if x >= 0 and -1.0 if x < 0.
indicator(float) - Static method in class org.apache.commons.math.util.MathUtils
  For a float value x, this method returns +1.0F if x >= 0 and -1.0F if x < 0.
indicator(byte) - Static method in class org.apache.commons.math.util.MathUtils
  For a byte value x, this method returns (byte)(+1) if x >= 0 and (byte)(-1) if x < 0.
indicator(short) - Static method in class org.apache.commons.math.util.MathUtils
  For a short value x, this method returns (short)(+1) if x >= 0 and (short)(-1) if x < 0.
indicator(int) - Static method in class org.apache.commons.math.util.MathUtils
  For an int value x, this method returns +1 if x >= 0 and -1 if x < 0.
indicator(long) - Static method in class org.apache.commons.math.util.MathUtils
  For a long value x, this method returns +1L if x >= 0 and -1L if x < 0.
initialCapacity - Variable in class org.apache.commons.math.util.ResizableDoubleArray
  The initial capacity of the array.
internalArray - Variable in class org.apache.commons.math.util.ResizableDoubleArray
  The internal storage array.
interpolate(double[], double[]) - Method in class org.apache.commons.math.analysis.SplineInterpolator
  Computes an interpolating function for the data set.
interpolate(double[], double[]) - Method in interface org.apache.commons.math.analysis.UnivariateRealInterpolator
  Computes an interpolating function for the data set.
inverse() - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns the inverse of this matrix.
inverse() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns the inverse matrix if this matrix is invertible.
inverse() - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the inverse of this matrix.
inverse() - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Returns the inverse matrix if this matrix is invertible.
inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.AbstractContinuousDistribution
  For this distribution, X, this method returns the critical point x, such that P(X < x) = `p`.
inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
  For a random variable X whose values are distributed according to this distribution, this method returns the largest x, such that P(X ≤ x) ≤ `p`.
inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
  For this distribution, X, this method returns the largest x, such that P(X ≤ x) ≤ `p`.
inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  For this distribution, X, this method returns the critical point x, such that P(X < x) = `p`.
inverseCumulativeProbability(double) - Method in interface org.apache.commons.math.distribution.ContinuousDistribution
  For this disbution, X, this method returns x such that P(X < x) = p.
inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
  For this distribution, X, this method returns the critical point x, such that P(X < x) = `p`.
inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
  For this distribution, X, this method returns the critical point x, such that P(X < x) = `p`.
inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
  For this distribution, X, this method returns the critical point x, such that P(X < x) = `p`.
inverseCumulativeProbability(double) - Method in interface org.apache.commons.math.distribution.IntegerDistribution
  For this distribution, X, this method returns the largest x such that P(X ≤ x) <= p.
inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
  For this distribution, X, this method returns the critical point x, such that P(X < x) = `p`.
inverseCumulativeProbability(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
  For this distribution, X, this method returns the critical point x, such that P(X < x) = `p`.
isBiasCorrected() - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
isBiasCorrected() - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
isBracketing(double, double, UnivariateRealFunction) - Method in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Returns true iff the function takes opposite signs at the endpoints.
isLoaded() - Method in interface org.apache.commons.math.random.EmpiricalDistribution
  Property indicating whether or not the distribution has been loaded.
isLoaded() - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Property indicating whether or not the distribution has been loaded.
isNaN() - Method in class org.apache.commons.math.complex.Complex
  Returns true if this complex number is the special Not-a-Number (NaN) value.
isSequence(double, double, double) - Method in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Returns true if the arguments form a (strictly) increasing sequence
isSingular() - Method in interface org.apache.commons.math.linear.BigMatrix
  Is this a singular matrix?
isSingular() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Is this a singular matrix?
isSingular() - Method in interface org.apache.commons.math.linear.RealMatrix
  Is this a singular matrix?
isSingular() - Method in class org.apache.commons.math.linear.RealMatrixImpl
isSquare() - Method in interface org.apache.commons.math.linear.BigMatrix
  Is this a square matrix?
isSquare() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Is this a square matrix?
isSquare() - Method in interface org.apache.commons.math.linear.RealMatrix
  Is this a square matrix?
isSquare() - Method in class org.apache.commons.math.linear.RealMatrixImpl
iterationCount - Variable in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  The last iteration count.

## K

Kurtosis - class org.apache.commons.math.stat.descriptive.moment.Kurtosis.
  Computes the Kurtosis of the available values.
Kurtosis() - Constructor for class org.apache.commons.math.stat.descriptive.moment.Kurtosis
  Construct a Kurtosis
Kurtosis(FourthMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.Kurtosis
  Construct a Kurtosis from an external moment

## L

load(double[]) - Method in interface org.apache.commons.math.random.EmpiricalDistribution
  Computes the empirical distribution from the provided array of numbers.
load(File) - Method in interface org.apache.commons.math.random.EmpiricalDistribution
  Computes the empirical distribution from the input file.
load(URL) - Method in interface org.apache.commons.math.random.EmpiricalDistribution
  Computes the empirical distribution using data read from a URL.
load(double[]) - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Computes the empirical distribution from the provided array of numbers.
load(URL) - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Computes the empirical distribution using data read from a URL.
load(File) - Method in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Computes the empirical distribution from the input file.
log(Complex) - Static method in class org.apache.commons.math.complex.ComplexUtils
  Compute the natural logarithm for the given complex argument.
logBeta(double, double) - Static method in class org.apache.commons.math.special.Beta
  Returns the natural logarithm of the beta function B(a, b).
logBeta(double, double, double, int) - Static method in class org.apache.commons.math.special.Beta
  Returns the natural logarithm of the beta function B(a, b).
logGamma(double) - Static method in class org.apache.commons.math.special.Gamma
  Returns the natural logarithm of the gamma function Γ(x).
luDecompose() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Computes a new LU decompostion for this matrix, storing the result for use by other methods.
luDecompose() - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Computes a new LU decompostion for this matrix, storing the result for use by other methods.

## M

MULTIPLICATIVE_MODE - Static variable in class org.apache.commons.math.util.ResizableDoubleArray
  multiplicative expansion mode
MathConfigurationException - exception org.apache.commons.math.MathConfigurationException.
  Signals a configuration problem with any of the factory methods.
MathConfigurationException() - Constructor for class org.apache.commons.math.MathConfigurationException
  Default constructor.
MathConfigurationException(String) - Constructor for class org.apache.commons.math.MathConfigurationException
  Construct an exception with the given message.
MathConfigurationException(String, Throwable) - Constructor for class org.apache.commons.math.MathConfigurationException
  Construct an exception with the given message and root cause.
MathConfigurationException(Throwable) - Constructor for class org.apache.commons.math.MathConfigurationException
  Construct an exception with the given root cause.
MathException - exception org.apache.commons.math.MathException.
  Base class for commons-math checked exceptions.
MathException() - Constructor for class org.apache.commons.math.MathException
  Constructs a new `MathException` with no detail message.
MathException(String) - Constructor for class org.apache.commons.math.MathException
  Constructs a new `MathException` with specified detail message.
MathException(Throwable) - Constructor for class org.apache.commons.math.MathException
  Constructs a new `MathException` with specified nested `Throwable` root cause.
MathException(String, Throwable) - Constructor for class org.apache.commons.math.MathException
  Constructs a new `MathException` with specified detail message and nested `Throwable` root cause.
MathUtils - class org.apache.commons.math.util.MathUtils.
  Some useful additions to the built-in functions in `Math`.
MatrixIndexException - exception org.apache.commons.math.linear.MatrixIndexException.
  Thrown when an operation addresses a matrix coordinate (row,col) which is outside of the dimensions of a matrix.
MatrixIndexException() - Constructor for class org.apache.commons.math.linear.MatrixIndexException
  Default constructor.
MatrixIndexException(String) - Constructor for class org.apache.commons.math.linear.MatrixIndexException
  Construct an exception with the given message and root cause.
MatrixUtils - class org.apache.commons.math.linear.MatrixUtils.
  A collection of static methods that operate on or return matrices.
MatrixUtils() - Constructor for class org.apache.commons.math.linear.MatrixUtils
  Default constructor.
Max - class org.apache.commons.math.stat.descriptive.rank.Max.
  Returns the maximum of the available values.
Max() - Constructor for class org.apache.commons.math.stat.descriptive.rank.Max
  Create a Max instance
Mean - class org.apache.commons.math.stat.descriptive.moment.Mean.
  Returns the arithmetic mean of the available values.
Mean() - Constructor for class org.apache.commons.math.stat.descriptive.moment.Mean
  Constructs a Mean.
Mean(FirstMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.Mean
  Constructs a Mean with an External Moment.
Median - class org.apache.commons.math.stat.descriptive.rank.Median.
  Returns the median of the available values.
Median() - Constructor for class org.apache.commons.math.stat.descriptive.rank.Median
  Default constructor.
Min - class org.apache.commons.math.stat.descriptive.rank.Min.
  Returns the minimum of the available values.
Min() - Constructor for class org.apache.commons.math.stat.descriptive.rank.Min
  Create a Min instance
m1 - Variable in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
  First moment of values that have been added
m2 - Variable in class org.apache.commons.math.stat.descriptive.moment.SecondMoment
  second moment of values that have been added
m3 - Variable in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
  third moment of values that have been added
m4 - Variable in class org.apache.commons.math.stat.descriptive.moment.FourthMoment
  fourth moment of values that have been added
max(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the maximum of the entries in the input array, or `Double.NaN` if the array is empty.
max(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the maximum of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
max - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
  max of values that have been added
maximalIterationCount - Variable in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Maximum number of iterations.
mean(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the arithmetic mean of the entries in the input array, or `Double.NaN` if the array is empty.
mean(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the arithmetic mean of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
mean - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
  mean of values that have been added
meanDifference(double[], double[]) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the mean of the (signed) differences between corresponding elements of the input arrays -- i.e., sum(sample1[i] - sample2[i]) / sample1.length.
midpoint(double, double) - Static method in class org.apache.commons.math.analysis.UnivariateRealSolverUtils
  Compute the midpoint of two values.
min(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the minimum of the entries in the input array, or `Double.NaN` if the array is empty.
min(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the minimum of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
min - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
  min of values that have been added
moment - Variable in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
  Fourth Moment on which this statistic is based
moment - Variable in class org.apache.commons.math.stat.descriptive.moment.Mean
  First moment on which this statistic is based.
moment - Variable in class org.apache.commons.math.stat.descriptive.moment.Skewness
  Third moment on which this statistic is based
moment - Variable in class org.apache.commons.math.stat.descriptive.moment.Variance
  SecondMoment is used in incremental calculation of Variance
multiply(Complex) - Method in class org.apache.commons.math.complex.Complex
  Return the product of this complex number and the given complex number.
multiply(BigMatrix) - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns the result of postmultiplying this by m.
multiply(BigMatrix) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns the result of postmultiplying this by `m`.
multiply(RealMatrix) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the result of postmultiplying this by m.
multiply(RealMatrix) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Returns the result of postmultiplying this by `m`.

## N

NaN - Static variable in class org.apache.commons.math.complex.Complex
  A complex number representing "(Double.NaN) + (Double.NaN)i"
NewtonSolver - class org.apache.commons.math.analysis.NewtonSolver.
  Implements Newton's Method for finding zeros of real univariate functions.
NewtonSolver(DifferentiableUnivariateRealFunction) - Constructor for class org.apache.commons.math.analysis.NewtonSolver
  Construct a solver for the given function.
NormalDistribution - interface org.apache.commons.math.distribution.NormalDistribution.
  Normal (Gauss) Distribution.
NormalDistributionImpl - class org.apache.commons.math.distribution.NormalDistributionImpl.
  Default implementation of `NormalDistribution`.
NormalDistributionImpl(double, double) - Constructor for class org.apache.commons.math.distribution.NormalDistributionImpl
  Create a normal distribution using the given mean and standard deviation.
NormalDistributionImpl() - Constructor for class org.apache.commons.math.distribution.NormalDistributionImpl
  Creates normal distribution with the mean equal to zero and standard deviation equal to one.
NumberTransformer - interface org.apache.commons.math.util.NumberTransformer.
  Subclasses implementing this interface can transform Objects to doubles.
n - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
  count of values that have been added
n - Variable in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
  Count of values that have been added
nDev - Variable in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
  Deviation of most recently added value from previous first moment, normalized by previous sample size.
nDevSq - Variable in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
  Square of deviation of most recently added value from previous first moment, normalized by previous sample size.
negate() - Method in class org.apache.commons.math.complex.Complex
  Return the additive inverse of this complex number.
newBisectionSolver(UnivariateRealFunction) - Method in class org.apache.commons.math.analysis.UnivariateRealSolverFactory
  Create a new `UnivariateRealSolver` for the given function.
newBisectionSolver(UnivariateRealFunction) - Method in class org.apache.commons.math.analysis.UnivariateRealSolverFactoryImpl
  Create a new `UnivariateRealSolver` for the given function.
newBrentSolver(UnivariateRealFunction) - Method in class org.apache.commons.math.analysis.UnivariateRealSolverFactory
  Create a new `UnivariateRealSolver` for the given function.
newBrentSolver(UnivariateRealFunction) - Method in class org.apache.commons.math.analysis.UnivariateRealSolverFactoryImpl
  Create a new `UnivariateRealSolver` for the given function.
newDefaultSolver(UnivariateRealFunction) - Method in class org.apache.commons.math.analysis.UnivariateRealSolverFactory
  Create a new `UnivariateRealSolver` for the given function.
newDefaultSolver(UnivariateRealFunction) - Method in class org.apache.commons.math.analysis.UnivariateRealSolverFactoryImpl
  Create a new `UnivariateRealSolver` for the given function.
newInstance() - Static method in class org.apache.commons.math.analysis.UnivariateRealSolverFactory
  Create a new factory.
newInstance() - Static method in class org.apache.commons.math.distribution.DistributionFactory
  Create an instance of a `DistributionFactory`
newInstance(Class) - Static method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Create an instance of a `DescriptiveStatistics`
newInstance() - Static method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Create an instance of a `DescriptiveStatistics`
newInstance(Class) - Static method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Create an instance of a `SummaryStatistics`
newInstance() - Static method in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Create an instance of a `SummaryStatistics`
newNewtonSolver(DifferentiableUnivariateRealFunction) - Method in class org.apache.commons.math.analysis.UnivariateRealSolverFactory
  Create a new `UnivariateRealSolver` for the given function.
newNewtonSolver(DifferentiableUnivariateRealFunction) - Method in class org.apache.commons.math.analysis.UnivariateRealSolverFactoryImpl
  Create a new `UnivariateRealSolver` for the given function.
newSecantSolver(UnivariateRealFunction) - Method in class org.apache.commons.math.analysis.UnivariateRealSolverFactory
  Create a new `UnivariateRealSolver` for the given function.
newSecantSolver(UnivariateRealFunction) - Method in class org.apache.commons.math.analysis.UnivariateRealSolverFactoryImpl
  Create a new `UnivariateRealSolver` for the given function.
nextExponential(double) - Method in interface org.apache.commons.math.random.RandomData
  Generates a random value from the exponential distribution with expected value = `mean`.
nextExponential(double) - Method in class org.apache.commons.math.random.RandomDataImpl
  Returns a random value from an Exponential distribution with the given mean.
nextGaussian(double, double) - Method in interface org.apache.commons.math.random.RandomData
  Generates a random value from the Normal (or Gaussian) distribution with the given mean and standard deviation.
nextGaussian(double, double) - Method in class org.apache.commons.math.random.RandomDataImpl
  Generate a random value from a Normal (a.k.a.
nextHexString(int) - Method in interface org.apache.commons.math.random.RandomData
  Generates a random string of hex characters of length `len`.
nextHexString(int) - Method in class org.apache.commons.math.random.RandomDataImpl
  Algorithm Description: hex strings are generated using a 2-step process.
nextInt(int, int) - Method in interface org.apache.commons.math.random.RandomData
  Generates a uniformly distributed random integer between `lower` and `upper` (endpoints included).
nextInt(int, int) - Method in class org.apache.commons.math.random.RandomDataImpl
  Generate a random int value uniformly distributed between `lower` and `upper`, inclusive.
nextLong(long, long) - Method in interface org.apache.commons.math.random.RandomData
  Generates a uniformly distributed random long integer between `lower` and `upper` (endpoints included).
nextLong(long, long) - Method in class org.apache.commons.math.random.RandomDataImpl
  Generate a random long value uniformly distributed between `lower` and `upper`, inclusive.
nextPermutation(int, int) - Method in interface org.apache.commons.math.random.RandomData
  Generates an integer array of length `k` whose entries are selected randomly, without repetition, from the integers `0 through n-1` (inclusive).
nextPermutation(int, int) - Method in class org.apache.commons.math.random.RandomDataImpl
  Uses a 2-cycle permutation shuffle to generate a random permutation.
nextPoisson(double) - Method in interface org.apache.commons.math.random.RandomData
  Generates a random value from the Poisson distribution with the given mean.
nextPoisson(double) - Method in class org.apache.commons.math.random.RandomDataImpl
  Generates a random long value from the Poisson distribution with the given mean.
nextSample(Collection, int) - Method in interface org.apache.commons.math.random.RandomData
  Returns an array of `k` objects selected randomly from the Collection `c`.
nextSample(Collection, int) - Method in class org.apache.commons.math.random.RandomDataImpl
  Uses a 2-cycle permutation shuffle to generate a random permutation.
nextSecureHexString(int) - Method in interface org.apache.commons.math.random.RandomData
  Generates a random string of hex characters from a secure random sequence.
nextSecureHexString(int) - Method in class org.apache.commons.math.random.RandomDataImpl
  Algorithm Description: hex strings are generated in 40-byte segments using a 3-step process.
nextSecureInt(int, int) - Method in interface org.apache.commons.math.random.RandomData
  Generates a uniformly distributed random integer between `lower` and `upper` (endpoints included) from a secure random sequence.
nextSecureInt(int, int) - Method in class org.apache.commons.math.random.RandomDataImpl
  Generate a random int value uniformly distributed between `lower` and `upper`, inclusive.
nextSecureLong(long, long) - Method in interface org.apache.commons.math.random.RandomData
  Generates a random long integer between `lower` and `upper` (endpoints included).
nextSecureLong(long, long) - Method in class org.apache.commons.math.random.RandomDataImpl
  Generate a random long value uniformly distributed between `lower` and `upper`, inclusive.
nextUniform(double, double) - Method in interface org.apache.commons.math.random.RandomData
  Generates a uniformly distributed random value from the open interval (`lower`,`upper`) (i.e., endpoints excluded).
nextUniform(double, double) - Method in class org.apache.commons.math.random.RandomDataImpl
  Algorithm Description: scales the output of Random.nextDouble(), but rejects 0 values (i.e., will generate another random double if Random.nextDouble() returns 0).
normalApproximateProbability(int) - Method in interface org.apache.commons.math.distribution.PoissonDistribution
  Calculates the Poisson distribution function using a normal approximation.
normalApproximateProbability(int) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
  Calculates the Poisson distribution function using a normal approximation.
numElements - Variable in class org.apache.commons.math.util.ResizableDoubleArray
  The number of addressable elements in the array.

## O

ONE - Static variable in class org.apache.commons.math.complex.Complex
  A complex number representing "1.0 + 0.0i"
operate(BigDecimal[]) - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns the result of multiplying this by the vector `v`.
operate(BigDecimal[]) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns the result of multiplying this by the vector `v`.
operate(double[]) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns the result of multiplying this by the vector `v`.
operate(double[]) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the result of multiplying this by the vector `v`.
operate(double[]) - Method in class org.apache.commons.math.linear.RealMatrixImpl
org.apache.commons.math - package org.apache.commons.math
  Common classes used throughout the commons-math library.
org.apache.commons.math.analysis - package org.apache.commons.math.analysis
  Implementations of common numerical analysis procedures, including root finding and function interpolation.
org.apache.commons.math.complex - package org.apache.commons.math.complex
  Complex number type and implementations of complex transcendental functions.
org.apache.commons.math.distribution - package org.apache.commons.math.distribution
  Implementations of common discrete and continuous distributions.
org.apache.commons.math.linear - package org.apache.commons.math.linear
  Linear algebra support.
org.apache.commons.math.random - package org.apache.commons.math.random
  Random number and random data generators.
org.apache.commons.math.special - package org.apache.commons.math.special
  Implementations of special functions such as Beta and Gamma.
org.apache.commons.math.stat - package org.apache.commons.math.stat
  Data storage, manipulation and summary routines.
org.apache.commons.math.stat.descriptive - package org.apache.commons.math.stat.descriptive
  Generic univariate summary statistic objects.
org.apache.commons.math.stat.descriptive.moment - package org.apache.commons.math.stat.descriptive.moment
  Summary statistics based on moments.
org.apache.commons.math.stat.descriptive.rank - package org.apache.commons.math.stat.descriptive.rank
  Summary statistics based on ranks.
org.apache.commons.math.stat.descriptive.summary - package org.apache.commons.math.stat.descriptive.summary
  Other summary statistics.
org.apache.commons.math.stat.inference - package org.apache.commons.math.stat.inference
  Classes providing hypothesis testing and confidence interval construction.
org.apache.commons.math.stat.regression - package org.apache.commons.math.stat.regression
  Statistical routines involving multivariate data.
org.apache.commons.math.util - package org.apache.commons.math.util
  Convience routines and common data structure used throughout the commons-math library.

## P

Percentile - class org.apache.commons.math.stat.descriptive.rank.Percentile.
  Provides percentile computation.
Percentile() - Constructor for class org.apache.commons.math.stat.descriptive.rank.Percentile
  Constructs a Percentile with a default quantile value of 50.0.
Percentile(double) - Constructor for class org.apache.commons.math.stat.descriptive.rank.Percentile
  Constructs a Percentile with the specific quantile value.
PoissonDistribution - interface org.apache.commons.math.distribution.PoissonDistribution.
  Interface representing the Poisson Distribution.
PoissonDistributionImpl - class org.apache.commons.math.distribution.PoissonDistributionImpl.
  Implementation for the @link{PoissonDistribution}
PoissonDistributionImpl(double) - Constructor for class org.apache.commons.math.distribution.PoissonDistributionImpl
  Create a new Poisson distribution with the given the mean.
PolynomialFunction - class org.apache.commons.math.analysis.PolynomialFunction.
  Immutable representation of a real polynomial function with real coefficients.
PolynomialFunction(double[]) - Constructor for class org.apache.commons.math.analysis.PolynomialFunction
  Construct a polynomial with the given coefficients.
PolynomialSplineFunction - class org.apache.commons.math.analysis.PolynomialSplineFunction.
  Represents a polynomial spline function.
PolynomialSplineFunction(double[], PolynomialFunction[]) - Constructor for class org.apache.commons.math.analysis.PolynomialSplineFunction
  Construct a polynomial spline function with the given segment delimiters and interpolating polynomials.
Product - class org.apache.commons.math.stat.descriptive.summary.Product.
  Returns the product of the available values.
Product() - Constructor for class org.apache.commons.math.stat.descriptive.summary.Product
  Create a Product instance
pairedT(double[], double[]) - Method in interface org.apache.commons.math.stat.inference.TTest
  Computes a paired, 2-sample t-statistic based on the data in the input arrays.
pairedT(double[], double[]) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes a paired, 2-sample t-statistic based on the data in the input arrays.
pairedTTest(double[], double[]) - Method in interface org.apache.commons.math.stat.inference.TTest
  Returns the observed significance level, or p-value, associated with a paired, two-sample, two-tailed t-test based on the data in the input arrays.
pairedTTest(double[], double[], double) - Method in interface org.apache.commons.math.stat.inference.TTest
  Performs a paired t-test evaluating the null hypothesis that the mean of the paired differences between `sample1` and `sample2` is 0 in favor of the two-sided alternative that the mean paired difference is not equal to 0, with significance level `alpha`.
pairedTTest(double[], double[]) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Returns the observed significance level, or p-value, associated with a paired, two-sample, two-tailed t-test based on the data in the input arrays.
pairedTTest(double[], double[], double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Performs a paired t-test evaluating the null hypothesis that the mean of the paired differences between `sample1` and `sample2` is 0 in favor of the two-sided alternative that the mean paired difference is not equal to 0, with significance level `alpha`.
parse(String) - Method in class org.apache.commons.math.complex.ComplexFormat
  Parses a string to produce a `Complex` object.
parse(String, ParsePosition) - Method in class org.apache.commons.math.complex.ComplexFormat
  Parses a string to produce a `Complex` object.
parseObject(String, ParsePosition) - Method in class org.apache.commons.math.complex.ComplexFormat
  Parses a string to produce a object.
percentile(double[], double) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns an estimate of the `p`th percentile of the values in the `values` array.
percentile(double[], int, int, double) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns an estimate of the `p`th percentile of the values in the `values` array, starting with the element in (0-based) position `begin` in the array and including `length` values.
polynomialDerivative() - Method in class org.apache.commons.math.analysis.PolynomialFunction
  Returns the derivative as a PolynomialRealFunction
polynomialSplineDerivative() - Method in class org.apache.commons.math.analysis.PolynomialSplineFunction
  Returns the derivative of the polynomial spline function as a PolynomialSplineFunction
pow(Complex, Complex) - Static method in class org.apache.commons.math.complex.ComplexUtils
  Returns of value of `y` raised to the power of `x`.
preMultiply(BigMatrix) - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns the result premultiplying this by `m`.
preMultiply(BigDecimal[]) - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns the (row) vector result of premultiplying this by the vector `v`.
preMultiply(BigMatrix) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns the result premultiplying this by `m`.
preMultiply(BigDecimal[]) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns the (row) vector result of premultiplying this by the vector `v`.
preMultiply(RealMatrix) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the result premultiplying this by `m`.
preMultiply(double[]) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the (row) vector result of premultiplying this by the vector `v`.
preMultiply(RealMatrix) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Returns the result premultiplying this by `m`.
preMultiply(double[]) - Method in class org.apache.commons.math.linear.RealMatrixImpl
predict(double) - Method in class org.apache.commons.math.stat.regression.SimpleRegression
  Returns the "predicted" `y` value associated with the supplied `x` value, based on the data that has been added to the model when this method is activated.
printStackTrace() - Method in class org.apache.commons.math.MathException
  Prints the stack trace of this exception to the standard error stream.
printStackTrace(PrintStream) - Method in class org.apache.commons.math.MathException
  Prints the stack trace of this exception to the specified stream.
printStackTrace(PrintWriter) - Method in class org.apache.commons.math.MathException
  Prints the stack trace of this exception to the specified writer.
probability(double) - Method in class org.apache.commons.math.distribution.AbstractIntegerDistribution
  For a random variable X whose values are distributed according to this distribution, this method returns P(X = x).
probability(int) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
  For this disbution, X, this method returns P(X = x).
probability(double) - Method in interface org.apache.commons.math.distribution.DiscreteDistribution
  For a random variable X whose values are distributed according to this distribution, this method returns P(X = x).
probability(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  For this disbution, X, this method returns P(X = x).
probability(int) - Method in interface org.apache.commons.math.distribution.IntegerDistribution
  For a random variable X whose values are distributed according to this distribution, this method returns P(X = x).
probability(int) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
  The probability mass function P(X = x) for a Poisson distribution.
product(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the product of the entries in the input array, or `Double.NaN` if the array is empty.
product(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the product of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
putTransformer(Class, NumberTransformer) - Method in class org.apache.commons.math.util.TransformerMap
  Sets a Class to Transformer Mapping in the Map.

## R

REPLAY_MODE - Static variable in class org.apache.commons.math.random.ValueServer
  Replay data from valuesFilePath
RandomData - interface org.apache.commons.math.random.RandomData.
  Random data generation utilities
RandomDataImpl - class org.apache.commons.math.random.RandomDataImpl.
  Implements the `RandomData` interface using `Random` and `Random.SecureRandom` instances to generate data.
RandomDataImpl() - Constructor for class org.apache.commons.math.random.RandomDataImpl
  Construct a RandomDataImpl.
RealMatrix - interface org.apache.commons.math.linear.RealMatrix.
  Interface defining a real-valued matrix with basic algebraic operations.
RealMatrixImpl - class org.apache.commons.math.linear.RealMatrixImpl.
  Implementation for RealMatrix using a double[][] array to store entries and LU decompostion to support linear system solution and inverse.
RealMatrixImpl() - Constructor for class org.apache.commons.math.linear.RealMatrixImpl
  Creates a matrix with no data
RealMatrixImpl(int, int) - Constructor for class org.apache.commons.math.linear.RealMatrixImpl
  Create a new RealMatrix with the supplied row and column dimensions.
RealMatrixImpl(double[][]) - Constructor for class org.apache.commons.math.linear.RealMatrixImpl
  Create a new RealMatrix using the input array as the underlying data array.
RealMatrixImpl(double[]) - Constructor for class org.apache.commons.math.linear.RealMatrixImpl
  Create a new (column) RealMatrix using `v` as the data for the unique column of the `v.length x 1` matrix created.
ResizableDoubleArray - class org.apache.commons.math.util.ResizableDoubleArray.
  A variable length `DoubleArray` implementation that automatically handles expanding and contracting its internal storage array as elements are added and removed.
ResizableDoubleArray() - Constructor for class org.apache.commons.math.util.ResizableDoubleArray
  Create a ResizableArray with default properties.
ResizableDoubleArray(int) - Constructor for class org.apache.commons.math.util.ResizableDoubleArray
  Create a ResizableArray with the specified initial capacity.
ResizableDoubleArray(int, float) - Constructor for class org.apache.commons.math.util.ResizableDoubleArray
  Create a ResizableArray with the specified initial capacity and expansion factor.
ResizableDoubleArray(int, float, float) - Constructor for class org.apache.commons.math.util.ResizableDoubleArray
  Create a ResizableArray with the specified initialCapacity, expansionFactor, and contractionCriteria.
ResizableDoubleArray(int, float, float, int) - Constructor for class org.apache.commons.math.util.ResizableDoubleArray
  Create a ResizableArray with the specified properties.
reSeed(long) - Method in class org.apache.commons.math.random.RandomDataImpl
  Reseeds the random number generator with the supplied seed.
reSeed() - Method in class org.apache.commons.math.random.RandomDataImpl
  Reseeds the random number generator with the current time in milliseconds.
reSeedSecure() - Method in class org.apache.commons.math.random.RandomDataImpl
  Reseeds the secure random number generator with the current time in milliseconds.
reSeedSecure(long) - Method in class org.apache.commons.math.random.RandomDataImpl
  Reseeds the secure random number generator with the supplied seed.
real - Variable in class org.apache.commons.math.complex.Complex
  The real part.
regularizedBeta(double, double, double) - Static method in class org.apache.commons.math.special.Beta
  Returns the regularized beta function I(x, a, b).
regularizedBeta(double, double, double, double) - Static method in class org.apache.commons.math.special.Beta
  Returns the regularized beta function I(x, a, b).
regularizedBeta(double, double, double, int) - Static method in class org.apache.commons.math.special.Beta
  Returns the regularized beta function I(x, a, b).
regularizedBeta(double, double, double, double, int) - Static method in class org.apache.commons.math.special.Beta
  Returns the regularized beta function I(x, a, b).
regularizedGammaP(double, double) - Static method in class org.apache.commons.math.special.Gamma
  Returns the regularized gamma function P(a, x).
regularizedGammaP(double, double, double, int) - Static method in class org.apache.commons.math.special.Gamma
  Returns the regularized gamma function P(a, x).
regularizedGammaQ(double, double) - Static method in class org.apache.commons.math.special.Gamma
  Returns the regularized gamma function Q(a, x) = 1 - P(a, x).
regularizedGammaQ(double, double, double, int) - Static method in class org.apache.commons.math.special.Gamma
  Returns the regularized gamma function Q(a, x) = 1 - P(a, x).
relativeAccuracy - Variable in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Maximum relative error.
removeTransformer(Class) - Method in class org.apache.commons.math.util.TransformerMap
  Removes a Class to Transformer Mapping in the Map.
resetAbsoluteAccuracy() - Method in interface org.apache.commons.math.analysis.UnivariateRealSolver
  Reset the absolute accuracy to the default.
resetAbsoluteAccuracy() - Method in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Reset the absolute accuracy to the default.
resetFunctionValueAccuracy() - Method in interface org.apache.commons.math.analysis.UnivariateRealSolver
  Reset the actual function accuracy to the default.
resetFunctionValueAccuracy() - Method in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Reset the actual function accuracy to the default.
resetMaximalIterationCount() - Method in interface org.apache.commons.math.analysis.UnivariateRealSolver
  Reset the upper limit for the number of iterations to the default.
resetMaximalIterationCount() - Method in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Reset the upper limit for the number of iterations to the default.
resetRelativeAccuracy() - Method in interface org.apache.commons.math.analysis.UnivariateRealSolver
  Reset the relative accuracy to the default.
resetRelativeAccuracy() - Method in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Reset the relative accuracy to the default.
resetReplayFile() - Method in class org.apache.commons.math.random.ValueServer
  Resets REPLAY_MODE file pointer to the beginning of the `valuesFileURL`.
result - Variable in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  The last computed root.
resultComputed - Variable in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Indicates where a root has been computed.

## S

SecantSolver - class org.apache.commons.math.analysis.SecantSolver.
  Implements a modified version of the secant method for approximating a zero of a real univariate function.
SecantSolver(UnivariateRealFunction) - Constructor for class org.apache.commons.math.analysis.SecantSolver
  Construct a solver for the given function.
SecondMoment - class org.apache.commons.math.stat.descriptive.moment.SecondMoment.
  Computes a statistic related to the Second Central Moment.
SecondMoment() - Constructor for class org.apache.commons.math.stat.descriptive.moment.SecondMoment
  Create a SecondMoment instance
SimpleRegression - class org.apache.commons.math.stat.regression.SimpleRegression.
  Estimates an ordinary least squares regression model with one independent variable.
SimpleRegression() - Constructor for class org.apache.commons.math.stat.regression.SimpleRegression
  Create an empty SimpleRegression instance
Skewness - class org.apache.commons.math.stat.descriptive.moment.Skewness.
  Computes the skewness of the available values.
Skewness() - Constructor for class org.apache.commons.math.stat.descriptive.moment.Skewness
  Constructs a Skewness
Skewness(ThirdMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.Skewness
  Constructs a Skewness with an external moment
SplineInterpolator - class org.apache.commons.math.analysis.SplineInterpolator.
  Computes a natural (a.k.a.
SplineInterpolator() - Constructor for class org.apache.commons.math.analysis.SplineInterpolator
StandardDeviation - class org.apache.commons.math.stat.descriptive.moment.StandardDeviation.
  Computes the sample standard deviation.
StandardDeviation() - Constructor for class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Constructs a StandardDeviation.
StandardDeviation(SecondMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Constructs a StandardDeviation from an external second moment.
StandardDeviation(boolean) - Constructor for class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Contructs a StandardDeviation with the specified value for the `isBiasCorrected` property.
StandardDeviation(boolean, SecondMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Contructs a StandardDeviation with the specified value for the `isBiasCorrected` property and the supplied external moment.
StatUtils - class org.apache.commons.math.stat.StatUtils.
  StatUtils provides static methods for computing statistics based on data stored in double[] arrays.
StatisticalSummary - interface org.apache.commons.math.stat.descriptive.StatisticalSummary.
  Reporting interface for basic univariate statistics.
StatisticalSummaryValues - class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues.
  Value object representing the results of a univariate statistical summary.
StatisticalSummaryValues(double, double, long, double, double, double) - Constructor for class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
  Constructor
StorelessUnivariateStatistic - interface org.apache.commons.math.stat.descriptive.StorelessUnivariateStatistic.
  Extends the definition of `UnivariateStatistic` with `StorelessUnivariateStatistic.increment(double)` and `StorelessUnivariateStatistic.incrementAll(double[])` methods for adding values and updating internal state.
Sum - class org.apache.commons.math.stat.descriptive.summary.Sum.
  Returns the sum of the available values.
Sum() - Constructor for class org.apache.commons.math.stat.descriptive.summary.Sum
  Create a Sum instance
SumOfLogs - class org.apache.commons.math.stat.descriptive.summary.SumOfLogs.
  Returns the sum of the natural logs for this collection of values.
SumOfLogs() - Constructor for class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
  Create a SumOfLogs instance
SumOfSquares - class org.apache.commons.math.stat.descriptive.summary.SumOfSquares.
  Returns the sum of the squares of the available values.
SumOfSquares() - Constructor for class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
  Create a SumOfSquares instance
SummaryStatistics - class org.apache.commons.math.stat.descriptive.SummaryStatistics.
  Abstract factory class for univariate statistical summaries.
SummaryStatistics() - Constructor for class org.apache.commons.math.stat.descriptive.SummaryStatistics
SummaryStatisticsImpl - class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl.
  Provides a default `SummaryStatistics` implementation.
SummaryStatisticsImpl() - Constructor for class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
  Construct a SummaryStatistics
sampleStats - Variable in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Sample statistics
scalarAdd(BigDecimal) - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns the result of adding d to each entry of this.
scalarAdd(BigDecimal) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns the result of adding d to each entry of this.
scalarAdd(double) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the result of adding d to each entry of this.
scalarAdd(double) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Returns the result of adding d to each entry of this.
scalarMultiply(BigDecimal) - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns the result multiplying each entry of this by d.
scalarMultiply(BigDecimal) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns the result multiplying each entry of this by `d`
scalarMultiply(double) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the result multiplying each entry of this by d.
scalarMultiply(double) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Returns the result multiplying each entry of this by `d`
secondMoment - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
  SecondMoment is used to compute the mean and variance
serialVersionUID - Static variable in class org.apache.commons.math.ConvergenceException
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.FunctionEvaluationException
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.MathConfigurationException
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.MathException
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.analysis.BisectionSolver
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.analysis.BrentSolver
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.analysis.NewtonSolver
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.analysis.PolynomialFunction
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.analysis.PolynomialSplineFunction
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.analysis.SecantSolver
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.complex.Complex
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.complex.ComplexFormat
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.AbstractContinuousDistribution
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.AbstractDistribution
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.AbstractIntegerDistribution
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.BinomialDistributionImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.ExponentialDistributionImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.FDistributionImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.GammaDistributionImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.NormalDistributionImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.PoissonDistributionImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.distribution.TDistributionImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.linear.BigMatrixImpl
  Serialization id
serialVersionUID - Static variable in class org.apache.commons.math.linear.InvalidMatrixException
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.linear.MatrixIndexException
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.linear.RealMatrixImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.random.EmpiricalDistributionImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.random.RandomDataImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.Frequency
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.AbstractStorelessUnivariateStatistic
  Serialization UID
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
  Serialization UID
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Serialization UID
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatisticsImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.StatisticalSummaryValues
  Serialization id
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.SummaryStatistics
  Serialization UID
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.FirstMoment
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.FourthMoment
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.GeometricMean
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.Kurtosis
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.Mean
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.SecondMoment
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.Skewness
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.moment.Variance
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.rank.Max
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.rank.Median
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.rank.Min
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.rank.Percentile
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.summary.Product
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.summary.Sum
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.summary.SumOfLogs
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.descriptive.summary.SumOfSquares
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.stat.regression.SimpleRegression
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.util.ContinuedFraction
  Serialization UID
serialVersionUID - Static variable in class org.apache.commons.math.util.DefaultTransformer
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.util.ResizableDoubleArray
  Serializable version identifier
serialVersionUID - Static variable in class org.apache.commons.math.util.TransformerMap
  Serializable version identifier
setAbsoluteAccuracy(double) - Method in interface org.apache.commons.math.analysis.UnivariateRealSolver
  Set the absolute accuracy.
setAbsoluteAccuracy(double) - Method in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Set the absolute accuracy.
setAlpha(double) - Method in interface org.apache.commons.math.distribution.GammaDistribution
  Modify the shape parameter, alpha.
setAlpha(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
  Modify the shape parameter, alpha.
setBeta(double) - Method in interface org.apache.commons.math.distribution.GammaDistribution
  Modify the scale parameter, beta.
setBeta(double) - Method in class org.apache.commons.math.distribution.GammaDistributionImpl
  Modify the scale parameter, beta.
setBiasCorrected(boolean) - Method in class org.apache.commons.math.stat.descriptive.moment.StandardDeviation
setBiasCorrected(boolean) - Method in class org.apache.commons.math.stat.descriptive.moment.Variance
setContractionCriteria(float) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Sets the contraction criteria for this ExpandContractDoubleArray.
setDegreesOfFreedom(double) - Method in interface org.apache.commons.math.distribution.ChiSquaredDistribution
  Modify the degrees of freedom.
setDegreesOfFreedom(double) - Method in class org.apache.commons.math.distribution.ChiSquaredDistributionImpl
  Modify the degrees of freedom.
setDegreesOfFreedom(double) - Method in interface org.apache.commons.math.distribution.TDistribution
  Modify the degrees of freedom.
setDegreesOfFreedom(double) - Method in class org.apache.commons.math.distribution.TDistributionImpl
  Modify the degrees of freedom.
setDenominatorDegreesOfFreedom(double) - Method in interface org.apache.commons.math.distribution.FDistribution
  Modify the denominator degrees of freedom.
setDenominatorDegreesOfFreedom(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
  Modify the denominator degrees of freedom.
setElement(int, double) - Method in interface org.apache.commons.math.util.DoubleArray
  Sets the element at the specified index.
setElement(int, double) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Sets the element at the specified index.
setExpansionFactor(float) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Sets the expansionFactor.
setExpansionMode(int) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Sets the `expansionMode`.
setFunctionValueAccuracy(double) - Method in interface org.apache.commons.math.analysis.UnivariateRealSolver
  Set the function value accuracy.
setFunctionValueAccuracy(double) - Method in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Set the function value accuracy.
setImaginaryCharacter(String) - Method in class org.apache.commons.math.complex.ComplexFormat
  Modify the imaginaryCharacter.
setImaginaryFormat(NumberFormat) - Method in class org.apache.commons.math.complex.ComplexFormat
  Modify the imaginaryFormat.
setInitialCapacity(int) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Sets the initial capacity.
setMaximalIterationCount(int) - Method in interface org.apache.commons.math.analysis.UnivariateRealSolver
  Set the upper limit for the number of iterations.
setMaximalIterationCount(int) - Method in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Set the upper limit for the number of iterations.
setMean(double) - Method in interface org.apache.commons.math.distribution.ExponentialDistribution
  Modify the mean.
setMean(double) - Method in class org.apache.commons.math.distribution.ExponentialDistributionImpl
  Modify the mean.
setMean(double) - Method in interface org.apache.commons.math.distribution.NormalDistribution
  Modify the mean.
setMean(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
  Modify the mean.
setMean(double) - Method in interface org.apache.commons.math.distribution.PoissonDistribution
  Set the mean for the distribution.
setMean(double) - Method in class org.apache.commons.math.distribution.PoissonDistributionImpl
  Set the Poisson mean for the distribution.
setMode(int) - Method in class org.apache.commons.math.random.ValueServer
  Setter for property mode.
setMu(double) - Method in class org.apache.commons.math.random.ValueServer
  Setter for property mu.
setNumElements(int) - Method in class org.apache.commons.math.util.ResizableDoubleArray
  This function allows you to control the number of elements contained in this array, and can be used to "throw out" the last n values in an array.
setNumberOfSuccesses(int) - Method in interface org.apache.commons.math.distribution.HypergeometricDistribution
  Modify the number of successes.
setNumberOfSuccesses(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Modify the number of successes.
setNumberOfTrials(int) - Method in interface org.apache.commons.math.distribution.BinomialDistribution
  Change the number of trials for this distribution.
setNumberOfTrials(int) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
  Change the number of trials for this distribution.
setNumeratorDegreesOfFreedom(double) - Method in interface org.apache.commons.math.distribution.FDistribution
  Modify the numerator degrees of freedom.
setNumeratorDegreesOfFreedom(double) - Method in class org.apache.commons.math.distribution.FDistributionImpl
  Modify the numerator degrees of freedom.
setPopulationSize(int) - Method in interface org.apache.commons.math.distribution.HypergeometricDistribution
  Modify the population size.
setPopulationSize(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Modify the population size.
setProbabilityOfSuccess(double) - Method in interface org.apache.commons.math.distribution.BinomialDistribution
  Change the probability of success for this distribution.
setProbabilityOfSuccess(double) - Method in class org.apache.commons.math.distribution.BinomialDistributionImpl
  Change the probability of success for this distribution.
setQuantile(double) - Method in class org.apache.commons.math.stat.descriptive.rank.Percentile
  Sets the value of the quantile field (determines what percentile is computed when evaluate() is called with no quantile argument).
setRealFormat(NumberFormat) - Method in class org.apache.commons.math.complex.ComplexFormat
  Modify the realFormat.
setRelativeAccuracy(double) - Method in interface org.apache.commons.math.analysis.UnivariateRealSolver
  Set the relative accuracy.
setRelativeAccuracy(double) - Method in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Set the relative accuracy.
setResult(double, int) - Method in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Convenience function for implementations.
setRoundingMode(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Sets the rounding mode for decimal divisions.
setSampleSize(int) - Method in interface org.apache.commons.math.distribution.HypergeometricDistribution
  Modify the sample size.
setSampleSize(int) - Method in class org.apache.commons.math.distribution.HypergeometricDistributionImpl
  Modify the sample size.
setScale(int) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Sets the scale for division operations.
setSecureAlgorithm(String, String) - Method in class org.apache.commons.math.random.RandomDataImpl
  Sets the PRNG algorithm for the underlying SecureRandom instance using the Security Provider API.
setSigma(double) - Method in class org.apache.commons.math.random.ValueServer
  Setter for property sigma.
setStandardDeviation(double) - Method in interface org.apache.commons.math.distribution.NormalDistribution
  Modify the standard deviation.
setStandardDeviation(double) - Method in class org.apache.commons.math.distribution.NormalDistributionImpl
  Modify the standard deviation.
setValuesFileURL(String) - Method in class org.apache.commons.math.random.ValueServer
  Sets the `valuesFileURL` using a string URL representation
setValuesFileURL(URL) - Method in class org.apache.commons.math.random.ValueServer
  Sets the `valuesFileURL`
setWindowSize(int) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  WindowSize controls the number of values which contribute to the values returned by Univariate.
setWindowSize(int) - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatisticsImpl
sign(double) - Static method in class org.apache.commons.math.util.MathUtils
  Returns the sign for double precision `x`.
sign(float) - Static method in class org.apache.commons.math.util.MathUtils
  Returns the sign for float value `x`.
sign(byte) - Static method in class org.apache.commons.math.util.MathUtils
  Returns the sign for byte value `x`.
sign(short) - Static method in class org.apache.commons.math.util.MathUtils
  Returns the sign for short value `x`.
sign(int) - Static method in class org.apache.commons.math.util.MathUtils
  Returns the sign for int value `x`.
sign(long) - Static method in class org.apache.commons.math.util.MathUtils
  Returns the sign for long value `x`.
sin(Complex) - Static method in class org.apache.commons.math.complex.ComplexUtils
  Compute the sine for the given complex argument.
sinh(Complex) - Static method in class org.apache.commons.math.complex.ComplexUtils
  Compute the hyperbolic sine for the given complex argument.
sinh(double) - Static method in class org.apache.commons.math.util.MathUtils
  Returns the hyperbolic sine of x.
solve(double, double, double) - Method in class org.apache.commons.math.analysis.BisectionSolver
  Find a zero in the given interval.
solve(double, double) - Method in class org.apache.commons.math.analysis.BisectionSolver
  Find a zero root in the given interval.
solve(double, double, double) - Method in class org.apache.commons.math.analysis.BrentSolver
  Find a zero in the given interval.
solve(double, double) - Method in class org.apache.commons.math.analysis.BrentSolver
  Find a zero in the given interval.
solve(double, double) - Method in class org.apache.commons.math.analysis.NewtonSolver
  Find a zero near the midpoint of `min` and `max`.
solve(double, double, double) - Method in class org.apache.commons.math.analysis.NewtonSolver
  Find a zero near the value `startValue`.
solve(double, double, double) - Method in class org.apache.commons.math.analysis.SecantSolver
  Find a zero in the given interval.
solve(double, double) - Method in class org.apache.commons.math.analysis.SecantSolver
  Find a zero in the given interval.
solve(double, double) - Method in interface org.apache.commons.math.analysis.UnivariateRealSolver
  Solve for a zero root in the given interval.
solve(double, double, double) - Method in interface org.apache.commons.math.analysis.UnivariateRealSolver
  Solve for a zero in the given interval, start at startValue.
solve(UnivariateRealFunction, double, double) - Static method in class org.apache.commons.math.analysis.UnivariateRealSolverUtils
  Convenience method to find a zero of a univariate real function.
solve(UnivariateRealFunction, double, double, double) - Static method in class org.apache.commons.math.analysis.UnivariateRealSolverUtils
  Convenience method to find a zero of a univariate real function.
solve(BigDecimal[]) - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns the solution vector for a linear system with coefficient matrix = this and constant vector = `b`.
solve(BigMatrix) - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns a matrix of (column) solution vectors for linear systems with coefficient matrix = this and constant vectors = columns of `b`.
solve(BigDecimal[]) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns a matrix of (column) solution vectors for linear systems with coefficient matrix = this and constant vectors = columns of `b`.
solve(double[]) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns a matrix of (column) solution vectors for linear systems with coefficient matrix = this and constant vectors = columns of `b`.
solve(BigMatrix) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns a matrix of (column) solution vectors for linear systems with coefficient matrix = this and constant vectors = columns of `b`.
solve(double[]) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the solution vector for a linear system with coefficient matrix = this and constant vector = `b`.
solve(RealMatrix) - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns a matrix of (column) solution vectors for linear systems with coefficient matrix = this and constant vectors = columns of `b`.
solve(double[]) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Returns a matrix of (column) solution vectors for linear systems with coefficient matrix = this and constant vectors = columns of `b`.
solve(RealMatrix) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Returns a matrix of (column) solution vectors for linear systems with coefficient matrix = this and constant vectors = columns of `b`.
sqrt(Complex) - Static method in class org.apache.commons.math.complex.ComplexUtils
  Compute the squre root for the given complex argument.
sqrt1z(Complex) - Static method in class org.apache.commons.math.complex.ComplexUtils
  Compute the squre root of 1 - `z`2 for the given complex argument.
start() - Method in class org.apache.commons.math.util.ResizableDoubleArray
  Returns the starting index of the internal array.
startIndex - Variable in class org.apache.commons.math.util.ResizableDoubleArray
  The position of the first addressable element in the internal storage array.
subtract(Complex) - Method in class org.apache.commons.math.complex.Complex
  Return the difference between this complex number and the given complex number.
subtract(BigMatrix) - Method in interface org.apache.commons.math.linear.BigMatrix
  Compute this minus m.
subtract(BigMatrix) - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Compute this minus `m`.
subtract(RealMatrix) - Method in interface org.apache.commons.math.linear.RealMatrix
  Compute this minus m.
subtract(RealMatrix) - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Compute this minus `m`.
sum(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the sum of the values in the input array, or `Double.NaN` if the array is empty.
sum(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the sum of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
sum - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
  sum of values that have been added
sumDifference(double[], double[]) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the sum of the (signed) differences between corresponding elements of the input arrays -- i.e., sum(sample1[i] - sample2[i]).
sumLog(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the sum of the natural logs of the entries in the input array, or `Double.NaN` if the array is empty.
sumLog(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the sum of the natural logs of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
sumLog - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
  sumLog of values that have been added
sumSq(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the sum of the squares of the entries in the input array, or `Double.NaN` if the array is empty.
sumSq(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the sum of the squares of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
sumsq - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
  sum of the square of each value that has been added

## T

TDistribution - interface org.apache.commons.math.distribution.TDistribution.
  Student's t-Distribution.
TDistributionImpl - class org.apache.commons.math.distribution.TDistributionImpl.
  Default implementation of `TDistribution`.
TDistributionImpl(double) - Constructor for class org.apache.commons.math.distribution.TDistributionImpl
  Create a t distribution using the given degrees of freedom.
TOO_SMALL - Static variable in class org.apache.commons.math.linear.BigMatrixImpl
  Bound to determine effective singularity in LU decomposition
TOO_SMALL - Static variable in class org.apache.commons.math.linear.RealMatrixImpl
  Bound to determine effective singularity in LU decomposition
TTest - interface org.apache.commons.math.stat.inference.TTest.
  An interface for Student's t-tests.
TTestImpl - class org.apache.commons.math.stat.inference.TTestImpl.
  Implements t-test statistics defined in the `TTest` interface.
TTestImpl() - Constructor for class org.apache.commons.math.stat.inference.TTestImpl
  Default constructor.
ThirdMoment - class org.apache.commons.math.stat.descriptive.moment.ThirdMoment.
  Computes a statistic related to the Third Central Moment.
ThirdMoment() - Constructor for class org.apache.commons.math.stat.descriptive.moment.ThirdMoment
  Create a FourthMoment instance
TransformerMap - class org.apache.commons.math.util.TransformerMap.
  This TansformerMap automates the transformation of of mixed object types.
TransformerMap() - Constructor for class org.apache.commons.math.util.TransformerMap
t(double, double[]) - Method in interface org.apache.commons.math.stat.inference.TTest
  Computes a t statistic given observed values and a comparison constant.
t(double, StatisticalSummary) - Method in interface org.apache.commons.math.stat.inference.TTest
  Computes a t statistic to use in comparing the mean of the dataset described by `sampleStats` to `mu`.
t(double[], double[]) - Method in interface org.apache.commons.math.stat.inference.TTest
  Computes a 2-sample t statistic, without the hypothesis of equal subpopulation variances.
t(StatisticalSummary, StatisticalSummary) - Method in interface org.apache.commons.math.stat.inference.TTest
  Computes a 2-sample t statistic , comparing the means of the datasets described by two `StatisticalSummary` instances, without the assumption of equal subpopulation variances.
t(double, double[]) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes a t statistic given observed values and a comparison constant.
t(double, StatisticalSummary) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes a t statistic to use in comparing the mean of the dataset described by `sampleStats` to `mu`.
t(double[], double[]) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes a 2-sample t statistic, without the hypothesis of equal subpopulation variances.
t(StatisticalSummary, StatisticalSummary) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes a 2-sample t statistic , comparing the means of the datasets described by two `StatisticalSummary` instances, without the assumption of equal subpopulation variances.
t(double, double, double, double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes t test statistic for 1-sample t-test.
t(double, double, double, double, double, double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes t test statistic for 2-sample t-test.
tTest(double, double[]) - Method in interface org.apache.commons.math.stat.inference.TTest
  Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the input array with the constant `mu`.
tTest(double, double[], double) - Method in interface org.apache.commons.math.stat.inference.TTest
  Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which `sample` is drawn equals `mu`.
tTest(double, StatisticalSummary) - Method in interface org.apache.commons.math.stat.inference.TTest
  Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the dataset described by `sampleStats` with the constant `mu`.
tTest(double, StatisticalSummary, double) - Method in interface org.apache.commons.math.stat.inference.TTest
  Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which the dataset described by `stats` is drawn equals `mu`.
tTest(double[], double[]) - Method in interface org.apache.commons.math.stat.inference.TTest
  Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays.
tTest(double[], double[], double) - Method in interface org.apache.commons.math.stat.inference.TTest
  Performs a two-sided t-test evaluating the null hypothesis that `sample1` and `sample2` are drawn from populations with the same mean, with significance level `alpha`.
tTest(StatisticalSummary, StatisticalSummary) - Method in interface org.apache.commons.math.stat.inference.TTest
  Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances.
tTest(StatisticalSummary, StatisticalSummary, double) - Method in interface org.apache.commons.math.stat.inference.TTest
  Performs a two-sided t-test evaluating the null hypothesis that `sampleStats1` and `sampleStats2` describe datasets drawn from populations with the same mean, with significance level `alpha`.
tTest(double, double[]) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the input array with the constant `mu`.
tTest(double, double[], double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which `sample` is drawn equals `mu`.
tTest(double, StatisticalSummary) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Returns the observed significance level, or p-value, associated with a one-sample, two-tailed t-test comparing the mean of the dataset described by `sampleStats` with the constant `mu`.
tTest(double, StatisticalSummary, double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Performs a two-sided t-test evaluating the null hypothesis that the mean of the population from which the dataset described by `stats` is drawn equals `mu`.
tTest(double[], double[]) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the input arrays.
tTest(double[], double[], double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Performs a two-sided t-test evaluating the null hypothesis that `sample1` and `sample2` are drawn from populations with the same mean, with significance level `alpha`.
tTest(StatisticalSummary, StatisticalSummary) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Returns the observed significance level, or p-value, associated with a two-sample, two-tailed t-test comparing the means of the datasets described by two StatisticalSummary instances.
tTest(StatisticalSummary, StatisticalSummary, double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Performs a two-sided t-test evaluating the null hypothesis that `sampleStats1` and `sampleStats2` describe datasets drawn from populations with the same mean, with significance level `alpha`.
tTest(double, double, double, double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes p-value for 2-sided, 1-sample t-test.
tTest(double, double, double, double, double, double) - Method in class org.apache.commons.math.stat.inference.TTestImpl
  Computes p-value for 2-sided, 2-sample t-test.
tan(Complex) - Static method in class org.apache.commons.math.complex.ComplexUtils
  Compute the tangent for the given complex argument.
tanh(Complex) - Static method in class org.apache.commons.math.complex.ComplexUtils
  Compute the hyperbolic tangent for the given complex argument.
test(double[], int, int) - Method in class org.apache.commons.math.stat.descriptive.AbstractUnivariateStatistic
  This method is used by `evaluate(double[], int, int)` methods to verify that the input parameters designate a subarray of positive length.
toString() - Method in class org.apache.commons.math.linear.BigMatrixImpl
toString() - Method in class org.apache.commons.math.linear.RealMatrixImpl
toString() - Method in class org.apache.commons.math.stat.Frequency
  Return a string representation of this frequency distribution.
toString() - Method in class org.apache.commons.math.stat.descriptive.DescriptiveStatistics
  Generates a text report displaying univariate statistics from values that have been added.
toString() - Method in class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
  Generates a text report displaying summary statistics from values that have been added.
transform(Object) - Method in class org.apache.commons.math.util.DefaultTransformer
transform(Object) - Method in interface org.apache.commons.math.util.NumberTransformer
  Implementing this interface provides a facility to transform from Object to Double.
transform(Object) - Method in class org.apache.commons.math.util.TransformerMap
  Attempts to transform the Object against the map of NumberTransformers.
transformers() - Method in class org.apache.commons.math.util.TransformerMap
  Returns the Set of NumberTransformers used as values in the map.
transpose() - Method in interface org.apache.commons.math.linear.BigMatrix
  Returns the transpose of this matrix.
transpose() - Method in class org.apache.commons.math.linear.BigMatrixImpl
  Returns the transpose matrix.
transpose() - Method in interface org.apache.commons.math.linear.RealMatrix
  Returns the transpose of this matrix.
transpose() - Method in class org.apache.commons.math.linear.RealMatrixImpl
  Returns the transpose matrix.

## U

UNIFORM_MODE - Static variable in class org.apache.commons.math.random.ValueServer
  Uniform random deviates with mean = mu
UnivariateRealFunction - interface org.apache.commons.math.analysis.UnivariateRealFunction.
  An interface representing a univariate real function.
UnivariateRealInterpolator - interface org.apache.commons.math.analysis.UnivariateRealInterpolator.
  Interface representing a univariate real interpolating function.
UnivariateRealSolver - interface org.apache.commons.math.analysis.UnivariateRealSolver.
  Interface for (univariate real) rootfinding algorithms.
UnivariateRealSolverFactory - class org.apache.commons.math.analysis.UnivariateRealSolverFactory.
  Abstract factory class used to create `UnivariateRealSolver` instances.
UnivariateRealSolverFactory() - Constructor for class org.apache.commons.math.analysis.UnivariateRealSolverFactory
  Default constructor.
UnivariateRealSolverFactoryImpl - class org.apache.commons.math.analysis.UnivariateRealSolverFactoryImpl.
  A concrete `UnivariateRealSolverFactory`.
UnivariateRealSolverFactoryImpl() - Constructor for class org.apache.commons.math.analysis.UnivariateRealSolverFactoryImpl
  Default constructor.
UnivariateRealSolverImpl - class org.apache.commons.math.analysis.UnivariateRealSolverImpl.
  Provide a default implementation for several functions useful to generic solvers.
UnivariateRealSolverImpl(UnivariateRealFunction, int, double) - Constructor for class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Construct a solver with given iteration count and accuracy.
UnivariateRealSolverUtils - class org.apache.commons.math.analysis.UnivariateRealSolverUtils.
  Utility routines for `UnivariateRealSolver` objects.
UnivariateStatistic - interface org.apache.commons.math.stat.descriptive.UnivariateStatistic.
  Base evaluation interface implemented by all statistics.

## V

ValueServer - class org.apache.commons.math.random.ValueServer.
  Generates values for use in simulation applications.
ValueServer() - Constructor for class org.apache.commons.math.random.ValueServer
  Creates new ValueServer
Variance - class org.apache.commons.math.stat.descriptive.moment.Variance.
  Computes the variance of the available values.
Variance() - Constructor for class org.apache.commons.math.stat.descriptive.moment.Variance
  Constructs a Variance with default (true) `isBiasCorrected` property.
Variance(SecondMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.Variance
  Constructs a Variance based on an external second moment.
Variance(boolean) - Constructor for class org.apache.commons.math.stat.descriptive.moment.Variance
  Constructs a Variance with the specified `isBiasCorrected` property
Variance(boolean, SecondMoment) - Constructor for class org.apache.commons.math.stat.descriptive.moment.Variance
  Constructs a Variance with the specified `isBiasCorrected` property and the supplied external second moment.
value(double) - Method in class org.apache.commons.math.analysis.PolynomialFunction
  Compute the value of the function for the given argument.
value(double) - Method in class org.apache.commons.math.analysis.PolynomialSplineFunction
  Compute the value for the function.
value(double) - Method in interface org.apache.commons.math.analysis.UnivariateRealFunction
  Compute the value for the function.
valuesIterator() - Method in class org.apache.commons.math.stat.Frequency
  Returns an Iterator over the set of values that have been added.
variance(double[]) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the variance of the entries in the input array, or `Double.NaN` if the array is empty.
variance(double[], int, int) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the variance of the entries in the specified portion of the input array, or `Double.NaN` if the designated subarray is empty.
variance(double[], double, int, int) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the variance of the entries in the specified portion of the input array, using the precomputed mean value.
variance(double[], double) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the variance of the entries in the input array, using the precomputed mean value.
variance - Variable in class org.apache.commons.math.stat.descriptive.SummaryStatisticsImpl
  variance of values that have been added
varianceDifference(double[], double[], double) - Static method in class org.apache.commons.math.stat.StatUtils
  Returns the variance of the (signed) differences between corresponding elements of the input arrays -- i.e., var(sample1[i] - sample2[i]).
verifyBracketing(double, double, UnivariateRealFunction) - Method in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Verifies that the endpoints specify an interval and the function takes opposite signs at the enpoints, throws IllegalArgumentException if not
verifyInterval(double, double) - Method in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Verifies that the endpoints specify an interval, throws IllegalArgumentException if not
verifySequence(double, double, double) - Method in class org.apache.commons.math.analysis.UnivariateRealSolverImpl
  Verifies that `lower < initial < upper` throws IllegalArgumentException if not

## W

windowSize - Variable in class org.apache.commons.math.stat.descriptive.DescriptiveStatisticsImpl
  hold the window size

A B C D E F G H I K L M N O P R S T U V W

Overview | Package | Class | Use | Tree | Deprecated | Index | Help
PREV NEXT | FRAMES NO FRAMES

Copyright © 2003-2004 The Apache Software Foundation. All Rights Reserved.