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 pth 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 quantileth 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 pth 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.a