| Package | Description | 
|---|---|
| org.apache.commons.math3 | Common classes used throughout the commons-math library. | 
| org.apache.commons.math3.analysis.function | 
      The  functionpackage contains function objects that wrap the
      methods contained inMath, as well as common
      mathematical functions such as the gaussian and sinc functions. | 
| org.apache.commons.math3.analysis.integration | Numerical integration (quadrature) algorithms for univariate real functions. | 
| org.apache.commons.math3.analysis.interpolation | Univariate real functions interpolation algorithms. | 
| org.apache.commons.math3.analysis.polynomials | Univariate real polynomials implementations, seen as differentiable
     univariate real functions. | 
| org.apache.commons.math3.analysis.solvers | Root finding algorithms, for univariate real functions. | 
| org.apache.commons.math3.complex | Complex number type and implementations of complex transcendental
     functions. | 
| org.apache.commons.math3.dfp | Decimal floating point library for Java | 
| org.apache.commons.math3.filter | Implementations of common discrete-time linear filters. | 
| org.apache.commons.math3.fraction | Fraction number type and fraction number formatting. | 
| org.apache.commons.math3.genetics | This package provides Genetic Algorithms components and implementations. | 
| org.apache.commons.math3.geometry.euclidean.twod.hull | 
 This package provides algorithms to generate the convex hull
 for a set of points in an two-dimensional euclidean space. | 
| org.apache.commons.math3.geometry.hull | 
 This package provides interfaces and classes related to the convex hull problem. | 
| org.apache.commons.math3.linear | Linear algebra support. | 
| org.apache.commons.math3.ml.clustering | Clustering algorithms. | 
| org.apache.commons.math3.optim.nonlinear.scalar | Algorithms for optimizing a scalar function. | 
| org.apache.commons.math3.optim.nonlinear.vector | Algorithms for optimizing a vector function. | 
| org.apache.commons.math3.random | Random number and random data generators. | 
| org.apache.commons.math3.stat | Data storage, manipulation and summary routines. | 
| org.apache.commons.math3.stat.clustering | All classes and sub-packages of this package are deprecated. | 
| org.apache.commons.math3.stat.descriptive | Generic univariate summary statistic objects. | 
| org.apache.commons.math3.stat.descriptive.moment | Summary statistics based on moments. | 
| org.apache.commons.math3.stat.descriptive.rank | Summary statistics based on ranks. | 
| org.apache.commons.math3.stat.descriptive.summary | Other summary statistics. | 
| org.apache.commons.math3.stat.inference | Classes providing hypothesis testing. | 
| org.apache.commons.math3.util | Convenience routines and common data structures used throughout the commons-math library. | 
| Modifier and Type | Method and Description | 
|---|---|
| T | FieldElement. add(T a)Compute this + a. | 
| T | FieldElement. divide(T a)Compute this ÷ a. | 
| T | FieldElement. multiply(T a)Compute this × a. | 
| T | FieldElement. subtract(T a)Compute this - a. | 
| Modifier and Type | Method and Description | 
|---|---|
| double[] | Logit.Parametric. gradient(double x,
        double... param)Computes the value of the gradient at  x. | 
| double[] | Logistic.Parametric. gradient(double x,
        double... param)Computes the value of the gradient at  x. | 
| double[] | HarmonicOscillator.Parametric. gradient(double x,
        double... param)Computes the value of the gradient at  x. | 
| double[] | Sigmoid.Parametric. gradient(double x,
        double... param)Computes the value of the gradient at  x. | 
| double[] | Gaussian.Parametric. gradient(double x,
        double... param)Computes the value of the gradient at  x. | 
| double | Logit.Parametric. value(double x,
     double... param)Computes the value of the logit at  x. | 
| double | Logistic.Parametric. value(double x,
     double... param)Computes the value of the sigmoid at  x. | 
| double | HarmonicOscillator.Parametric. value(double x,
     double... param)Computes the value of the harmonic oscillator at  x. | 
| double | Sigmoid.Parametric. value(double x,
     double... param)Computes the value of the sigmoid at  x. | 
| double | Gaussian.Parametric. value(double x,
     double... param)Computes the value of the Gaussian at  x. | 
| Constructor and Description | 
|---|
| StepFunction(double[] x,
            double[] y)Builds a step function from a list of arguments and the corresponding
 values. | 
| Modifier and Type | Method and Description | 
|---|---|
| double | UnivariateIntegrator. integrate(int maxEval,
         UnivariateFunction f,
         double min,
         double max)Integrate the function in the given interval. | 
| double | BaseAbstractUnivariateIntegrator. integrate(int maxEval,
         UnivariateFunction f,
         double lower,
         double upper)Integrate the function in the given interval. | 
| protected void | BaseAbstractUnivariateIntegrator. setup(int maxEval,
     UnivariateFunction f,
     double lower,
     double upper)Prepare for computation. | 
| Modifier and Type | Method and Description | 
|---|---|
| void | FieldHermiteInterpolator. addSamplePoint(T x,
              T[]... value)Add a sample point. | 
| T[][] | FieldHermiteInterpolator. derivatives(T x,
           int order)Interpolate value and first derivatives at a specified abscissa. | 
| MultivariateFunction | MultivariateInterpolator. interpolate(double[][] xval,
           double[] yval)Computes an interpolating function for the data set. | 
| MultivariateFunction | MicrosphereInterpolator. interpolate(double[][] xval,
           double[] yval)Deprecated.  Computes an interpolating function for the data set. | 
| MultivariateFunction | MicrosphereProjectionInterpolator. interpolate(double[][] xval,
           double[] yval)Computes an interpolating function for the data set. | 
| BicubicSplineInterpolatingFunction | SmoothingPolynomialBicubicSplineInterpolator. interpolate(double[] xval,
           double[] yval,
           double[][] fval)Deprecated.  Compute an interpolating function for the dataset. | 
| PiecewiseBicubicSplineInterpolatingFunction | PiecewiseBicubicSplineInterpolator. interpolate(double[] xval,
           double[] yval,
           double[][] fval)Compute an interpolating function for the dataset. | 
| T[] | FieldHermiteInterpolator. value(T x)Interpolate value at a specified abscissa. | 
| Constructor and Description | 
|---|
| MicrosphereInterpolatingFunction(double[][] xval,
                                double[] yval,
                                int brightnessExponent,
                                int microsphereElements,
                                UnitSphereRandomVectorGenerator rand)Deprecated.  | 
| PiecewiseBicubicSplineInterpolatingFunction(double[] x,
                                           double[] y,
                                           double[][] f) | 
| Modifier and Type | Method and Description | 
|---|---|
| protected static double[] | PolynomialFunction. differentiate(double[] coefficients)Returns the coefficients of the derivative of the polynomial with the given coefficients. | 
| protected static double | PolynomialFunction. evaluate(double[] coefficients,
        double argument)Uses Horner's Method to evaluate the polynomial with the given coefficients at
 the argument. | 
| static double | PolynomialFunctionNewtonForm. evaluate(double[] a,
        double[] c,
        double z)Evaluate the Newton polynomial using nested multiplication. | 
| DerivativeStructure | PolynomialFunction. value(DerivativeStructure t)Simple mathematical function. | 
| protected static void | PolynomialFunctionNewtonForm. verifyInputArray(double[] a,
                double[] c)Verifies that the input arrays are valid. | 
| Constructor and Description | 
|---|
| PolynomialFunction(double[] c)Construct a polynomial with the given coefficients. | 
| PolynomialFunctionNewtonForm(double[] a,
                            double[] c)Construct a Newton polynomial with the given a[] and c[]. | 
| PolynomialSplineFunction(double[] knots,
                        PolynomialFunction[] polynomials)Construct a polynomial spline function with the given segment delimiters
 and interpolating polynomials. | 
| Modifier and Type | Method and Description | 
|---|---|
| static double[] | UnivariateSolverUtils. bracket(UnivariateFunction function,
       double initial,
       double lowerBound,
       double upperBound)This method simply calls  bracket(function, initial, lowerBound, upperBound, q, r, maximumIterations)withqandrset to 1.0 andmaximumIterationsset toInteger.MAX_VALUE. | 
| static double[] | UnivariateSolverUtils. bracket(UnivariateFunction function,
       double initial,
       double lowerBound,
       double upperBound,
       int maximumIterations)This method simply calls  bracket(function, initial, lowerBound, upperBound, q, r, maximumIterations)withqandrset to 1.0. | 
| static boolean | UnivariateSolverUtils. isBracketing(UnivariateFunction function,
            double lower,
            double upper)Check whether the interval bounds bracket a root. | 
| protected void | BaseAbstractUnivariateSolver. setup(int maxEval,
     FUNC f,
     double min,
     double max,
     double startValue)Prepare for computation. | 
| T | FieldBracketingNthOrderBrentSolver. solve(int maxEval,
     RealFieldUnivariateFunction<T> f,
     T min,
     T max,
     AllowedSolution allowedSolution)Solve for a zero in the given interval. | 
| T | FieldBracketingNthOrderBrentSolver. solve(int maxEval,
     RealFieldUnivariateFunction<T> f,
     T min,
     T max,
     T startValue,
     AllowedSolution allowedSolution)Solve for a zero in the given interval, start at  startValue. | 
| static double | UnivariateSolverUtils. solve(UnivariateFunction function,
     double x0,
     double x1)Convenience method to find a zero of a univariate real function. | 
| static double | UnivariateSolverUtils. solve(UnivariateFunction function,
     double x0,
     double x1,
     double absoluteAccuracy)Convenience method to find a zero of a univariate real function. | 
| Complex[] | LaguerreSolver. solveAllComplex(double[] coefficients,
               double initial)Find all complex roots for the polynomial with the given
 coefficients, starting from the given initial value. | 
| Complex[] | LaguerreSolver. solveAllComplex(double[] coefficients,
               double initial,
               int maxEval)Find all complex roots for the polynomial with the given
 coefficients, starting from the given initial value. | 
| Complex | LaguerreSolver. solveComplex(double[] coefficients,
            double initial)Find a complex root for the polynomial with the given coefficients,
 starting from the given initial value. | 
| Complex | LaguerreSolver. solveComplex(double[] coefficients,
            double initial,
            int maxEval)Find a complex root for the polynomial with the given coefficients,
 starting from the given initial value. | 
| protected void | BaseAbstractUnivariateSolver. verifyBracketing(double lower,
                double upper)Check that the endpoints specify an interval and the function takes
 opposite signs at the endpoints. | 
| static void | UnivariateSolverUtils. verifyBracketing(UnivariateFunction function,
                double lower,
                double upper)Check that the endpoints specify an interval and the end points
 bracket a root. | 
| Modifier and Type | Method and Description | 
|---|---|
| Complex | Complex. add(Complex addend)Returns a  Complexwhose value is(this + addend). | 
| Complex | Complex. divide(Complex divisor)Returns a  Complexwhose value is(this / divisor). | 
| static ComplexFormat | ComplexFormat. getInstance(String imaginaryCharacter,
           Locale locale)Returns the default complex format for the given locale. | 
| Complex | Complex. multiply(Complex factor)Returns a  Complexwhose value isthis * factor. | 
| Complex | Complex. pow(Complex x)Returns of value of this complex number raised to the power of  x. | 
| Complex | Complex. subtract(Complex subtrahend)Returns a  Complexwhose value is(this - subtrahend). | 
| Constructor and Description | 
|---|
| ComplexFormat(NumberFormat format)Create an instance with a custom number format for both real and
 imaginary parts. | 
| ComplexFormat(NumberFormat realFormat,
             NumberFormat imaginaryFormat)Create an instance with a custom number format for the real part and a
 custom number format for the imaginary part. | 
| ComplexFormat(String imaginaryCharacter)Create an instance with a custom imaginary character, and the default
 number format for both real and imaginary parts. | 
| ComplexFormat(String imaginaryCharacter,
             NumberFormat format)Create an instance with a custom imaginary character, and a custom number
 format for both real and imaginary parts. | 
| ComplexFormat(String imaginaryCharacter,
             NumberFormat realFormat,
             NumberFormat imaginaryFormat)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. | 
| Modifier and Type | Method and Description | 
|---|---|
| Dfp | BracketingNthOrderBrentSolverDFP. solve(int maxEval,
     UnivariateDfpFunction f,
     Dfp min,
     Dfp max,
     AllowedSolution allowedSolution)Deprecated.  Solve for a zero in the given interval. | 
| Dfp | BracketingNthOrderBrentSolverDFP. solve(int maxEval,
     UnivariateDfpFunction f,
     Dfp min,
     Dfp max,
     Dfp startValue,
     AllowedSolution allowedSolution)Deprecated.  Solve for a zero in the given interval, start at  startValue. | 
| Modifier and Type | Method and Description | 
|---|---|
| void | KalmanFilter. correct(double[] z)Correct the current state estimate with an actual measurement. | 
| void | KalmanFilter. correct(RealVector z)Correct the current state estimate with an actual measurement. | 
| Constructor and Description | 
|---|
| DefaultMeasurementModel(double[][] measMatrix,
                       double[][] measNoise)Create a new  MeasurementModel, taking double arrays as input parameters for the
 respective measurement matrix and noise. | 
| DefaultProcessModel(double[][] stateTransition,
                   double[][] control,
                   double[][] processNoise)Create a new  ProcessModel, taking double arrays as input parameters. | 
| DefaultProcessModel(double[][] stateTransition,
                   double[][] control,
                   double[][] processNoise,
                   double[] initialStateEstimate,
                   double[][] initialErrorCovariance)Create a new  ProcessModel, taking double arrays as input parameters. | 
| KalmanFilter(ProcessModel process,
            MeasurementModel measurement)Creates a new Kalman filter with the given process and measurement models. | 
| Modifier and Type | Method and Description | 
|---|---|
| BigFraction | BigFraction. add(BigInteger bg)
 Adds the value of this fraction to the passed  BigInteger,
 returning the result in reduced form. | 
| Modifier and Type | Method and Description | 
|---|---|
| void | ListPopulation. setChromosomes(List<Chromosome> chromosomes)Deprecated. 
 use  ListPopulation.addChromosomes(Collection)instead | 
| Constructor and Description | 
|---|
| ElitisticListPopulation(List<Chromosome> chromosomes,
                       int populationLimit,
                       double elitismRate)Creates a new  ElitisticListPopulationinstance. | 
| ListPopulation(List<Chromosome> chromosomes,
              int populationLimit)Creates a new ListPopulation instance. | 
| Modifier and Type | Method and Description | 
|---|---|
| ConvexHull2D | ConvexHullGenerator2D. generate(Collection<Vector2D> points)Builds the convex hull from the set of input points. | 
| Modifier and Type | Method and Description | 
|---|---|
| ConvexHull<S,P> | ConvexHullGenerator. generate(Collection<P> points)Builds the convex hull from the set of input points. | 
| Modifier and Type | Method and Description | 
|---|---|
| FieldVector<T> | SparseFieldVector. append(T d)Construct a vector by appending a T to this vector. | 
| protected static void | PreconditionedIterativeLinearSolver. checkParameters(RealLinearOperator a,
               RealLinearOperator m,
               RealVector b,
               RealVector x0)Performs all dimension checks on the parameters of
  solveandsolveInPlace,
 and throws an exception if one of the checks fails. | 
| protected static void | IterativeLinearSolver. checkParameters(RealLinearOperator a,
               RealVector b,
               RealVector x0)Performs all dimension checks on the parameters of
  solveandsolveInPlace,
 and throws an exception if one of the checks fails. | 
| static void | MatrixUtils. checkSubMatrixIndex(AnyMatrix m,
                   int[] selectedRows,
                   int[] selectedColumns)Check if submatrix ranges indices are valid. | 
| protected void | AbstractFieldMatrix. checkSubMatrixIndex(int[] selectedRows,
                   int[] selectedColumns)Check if submatrix ranges indices are valid. | 
| void | AbstractRealMatrix. copySubMatrix(int[] selectedRows,
             int[] selectedColumns,
             double[][] destination)Copy a submatrix. | 
| void | RealMatrix. copySubMatrix(int[] selectedRows,
             int[] selectedColumns,
             double[][] destination)Copy a submatrix. | 
| void | AbstractFieldMatrix. copySubMatrix(int[] selectedRows,
             int[] selectedColumns,
             T[][] destination)Copy a submatrix. | 
| void | FieldMatrix. copySubMatrix(int[] selectedRows,
             int[] selectedColumns,
             T[][] destination)Copy a submatrix. | 
| static <T extends FieldElement<T>>  | MatrixUtils. createColumnFieldMatrix(T[] columnData)Creates a column  FieldMatrixusing the data from the input
 array. | 
| static RealMatrix | MatrixUtils. createColumnRealMatrix(double[] columnData)Creates a column  RealMatrixusing the data from the input
 array. | 
| static <T extends FieldElement<T>>  | MatrixUtils. createFieldMatrix(T[][] data)Returns a  FieldMatrixwhose entries are the the values in the
 the input array. | 
| static <T extends FieldElement<T>>  | MatrixUtils. createFieldVector(T[] data)Creates a  FieldVectorusing the data from the input array. | 
| static RealMatrix | MatrixUtils. createRealMatrix(double[][] data)Returns a  RealMatrixwhose entries are the the values in the
 the input array. | 
| static RealVector | MatrixUtils. createRealVector(double[] data)Creates a  RealVectorusing the data from the input array. | 
| static <T extends FieldElement<T>>  | MatrixUtils. createRowFieldMatrix(T[] rowData)Create a row  FieldMatrixusing the data from the input
 array. | 
| static RealMatrix | MatrixUtils. createRowRealMatrix(double[] rowData)Create a row  RealMatrixusing the data from the input
 array. | 
| protected static <T extends FieldElement<T>>  | AbstractFieldMatrix. extractField(T[][] d)Get the elements type from an array. | 
| RealMatrix | AbstractRealMatrix. getSubMatrix(int[] selectedRows,
            int[] selectedColumns)Gets a submatrix. | 
| FieldMatrix<T> | AbstractFieldMatrix. getSubMatrix(int[] selectedRows,
            int[] selectedColumns)Get a submatrix. | 
| RealMatrix | RealMatrix. getSubMatrix(int[] selectedRows,
            int[] selectedColumns)Gets a submatrix. | 
| FieldMatrix<T> | FieldMatrix. getSubMatrix(int[] selectedRows,
            int[] selectedColumns)Get a submatrix. | 
| static RealMatrix | MatrixUtils. inverse(RealMatrix matrix)Computes the inverse of the given matrix. | 
| static RealMatrix | MatrixUtils. inverse(RealMatrix matrix,
       double threshold)Computes the inverse of the given matrix. | 
| FieldVector<T> | FieldVector. mapAdd(T d)Map an addition operation to each entry. | 
| FieldVector<T> | SparseFieldVector. mapAdd(T d)Map an addition operation to each entry. | 
| FieldVector<T> | ArrayFieldVector. mapAdd(T d)Map an addition operation to each entry. | 
| FieldVector<T> | FieldVector. mapAddToSelf(T d)Map an addition operation to each entry. | 
| FieldVector<T> | SparseFieldVector. mapAddToSelf(T d)Map an addition operation to each entry. | 
| FieldVector<T> | ArrayFieldVector. mapAddToSelf(T d)Map an addition operation to each entry. | 
| FieldVector<T> | FieldVector. mapDivide(T d)Map a division operation to each entry. | 
| FieldVector<T> | SparseFieldVector. mapDivide(T d)Map a division operation to each entry. | 
| FieldVector<T> | ArrayFieldVector. mapDivide(T d)Map a division operation to each entry. | 
| FieldVector<T> | FieldVector. mapDivideToSelf(T d)Map a division operation to each entry. | 
| FieldVector<T> | SparseFieldVector. mapDivideToSelf(T d)Map a division operation to each entry. | 
| FieldVector<T> | ArrayFieldVector. mapDivideToSelf(T d)Map a division operation to each entry. | 
| FieldVector<T> | FieldVector. mapMultiply(T d)Map a multiplication operation to each entry. | 
| FieldVector<T> | SparseFieldVector. mapMultiply(T d)Map a multiplication operation to each entry. | 
| FieldVector<T> | ArrayFieldVector. mapMultiply(T d)Map a multiplication operation to each entry. | 
| FieldVector<T> | FieldVector. mapMultiplyToSelf(T d)Map a multiplication operation to each entry. | 
| FieldVector<T> | SparseFieldVector. mapMultiplyToSelf(T d)Map a multiplication operation to each entry. | 
| FieldVector<T> | ArrayFieldVector. mapMultiplyToSelf(T d)Map a multiplication operation to each entry. | 
| FieldVector<T> | FieldVector. mapSubtract(T d)Map a subtraction operation to each entry. | 
| FieldVector<T> | SparseFieldVector. mapSubtract(T d)Map a subtraction operation to each entry. | 
| FieldVector<T> | ArrayFieldVector. mapSubtract(T d)Map a subtraction operation to each entry. | 
| FieldVector<T> | FieldVector. mapSubtractToSelf(T d)Map a subtraction operation to each entry. | 
| FieldVector<T> | SparseFieldVector. mapSubtractToSelf(T d)Map a subtraction operation to each entry. | 
| FieldVector<T> | ArrayFieldVector. mapSubtractToSelf(T d)Map a subtraction operation to each entry. | 
| void | SparseFieldVector. setEntry(int index,
        T value)Set a single element. | 
| void | BlockRealMatrix. setSubMatrix(double[][] subMatrix,
            int row,
            int column)Replace the submatrix starting at  row, columnusing data in the
 inputsubMatrixarray. | 
| void | AbstractRealMatrix. setSubMatrix(double[][] subMatrix,
            int row,
            int column)Replace the submatrix starting at  row, columnusing data in the
 inputsubMatrixarray. | 
| void | RealMatrix. setSubMatrix(double[][] subMatrix,
            int row,
            int column)Replace the submatrix starting at  row, columnusing data in the
 inputsubMatrixarray. | 
| void | Array2DRowRealMatrix. setSubMatrix(double[][] subMatrix,
            int row,
            int column)Replace the submatrix starting at  row, columnusing data in the
 inputsubMatrixarray. | 
| void | Array2DRowFieldMatrix. setSubMatrix(T[][] subMatrix,
            int row,
            int column)Replace the submatrix starting at  (row, column)using data in the
 inputsubMatrixarray. | 
| void | AbstractFieldMatrix. setSubMatrix(T[][] subMatrix,
            int row,
            int column)Replace the submatrix starting at  (row, column)using data in the
 inputsubMatrixarray. | 
| void | BlockFieldMatrix. setSubMatrix(T[][] subMatrix,
            int row,
            int column)Replace the submatrix starting at  (row, column)using data in the
 inputsubMatrixarray. | 
| void | FieldMatrix. setSubMatrix(T[][] subMatrix,
            int row,
            int column)Replace the submatrix starting at  (row, column)using data in the
 inputsubMatrixarray. | 
| RealVector | SymmLQ. solve(RealLinearOperator a,
     RealLinearOperator m,
     RealVector b)Returns an estimate of the solution to the linear system A · x =
 b. | 
| RealVector | PreconditionedIterativeLinearSolver. solve(RealLinearOperator a,
     RealLinearOperator m,
     RealVector b)Returns an estimate of the solution to the linear system A · x =
 b. | 
| RealVector | SymmLQ. solve(RealLinearOperator a,
     RealLinearOperator m,
     RealVector b,
     boolean goodb,
     double shift)Returns an estimate of the solution to the linear system (A - shift
 · I) · x = b. | 
| RealVector | SymmLQ. solve(RealLinearOperator a,
     RealLinearOperator m,
     RealVector b,
     RealVector x)Returns an estimate of the solution to the linear system A · x =
 b. | 
| RealVector | PreconditionedIterativeLinearSolver. solve(RealLinearOperator a,
     RealLinearOperator m,
     RealVector b,
     RealVector x0)Returns an estimate of the solution to the linear system A · x =
 b. | 
| RealVector | SymmLQ. solve(RealLinearOperator a,
     RealVector b)Returns an estimate of the solution to the linear system A · x =
 b. | 
| RealVector | IterativeLinearSolver. solve(RealLinearOperator a,
     RealVector b)Returns an estimate of the solution to the linear system A · x =
 b. | 
| RealVector | PreconditionedIterativeLinearSolver. solve(RealLinearOperator a,
     RealVector b)Returns an estimate of the solution to the linear system A · x =
 b. | 
| RealVector | SymmLQ. solve(RealLinearOperator a,
     RealVector b,
     boolean goodb,
     double shift)Returns the solution to the system (A - shift · I) · x = b. | 
| RealVector | SymmLQ. solve(RealLinearOperator a,
     RealVector b,
     RealVector x)Returns an estimate of the solution to the linear system A · x =
 b. | 
| RealVector | IterativeLinearSolver. solve(RealLinearOperator a,
     RealVector b,
     RealVector x0)Returns an estimate of the solution to the linear system A · x =
 b. | 
| RealVector | PreconditionedIterativeLinearSolver. solve(RealLinearOperator a,
     RealVector b,
     RealVector x0)Returns an estimate of the solution to the linear system A · x =
 b. | 
| RealVector | SymmLQ. solveInPlace(RealLinearOperator a,
            RealLinearOperator m,
            RealVector b,
            RealVector x)Returns an estimate of the solution to the linear system A · x =
 b. | 
| RealVector | ConjugateGradient. solveInPlace(RealLinearOperator a,
            RealLinearOperator m,
            RealVector b,
            RealVector x0)Returns an estimate of the solution to the linear system A · x =
 b. | 
| abstract RealVector | PreconditionedIterativeLinearSolver. solveInPlace(RealLinearOperator a,
            RealLinearOperator m,
            RealVector b,
            RealVector x0)Returns an estimate of the solution to the linear system A · x =
 b. | 
| RealVector | SymmLQ. solveInPlace(RealLinearOperator a,
            RealLinearOperator m,
            RealVector b,
            RealVector x,
            boolean goodb,
            double shift)Returns an estimate of the solution to the linear system (A - shift
 · I) · x = b. | 
| RealVector | SymmLQ. solveInPlace(RealLinearOperator a,
            RealVector b,
            RealVector x)Returns an estimate of the solution to the linear system A · x =
 b. | 
| abstract RealVector | IterativeLinearSolver. solveInPlace(RealLinearOperator a,
            RealVector b,
            RealVector x0)Returns an estimate of the solution to the linear system A · x =
 b. | 
| RealVector | PreconditionedIterativeLinearSolver. solveInPlace(RealLinearOperator a,
            RealVector b,
            RealVector x0)Returns an estimate of the solution to the linear system A · x =
 b. | 
| Constructor and Description | 
|---|
| Array2DRowFieldMatrix(Field<T> field,
                     T[][] d)Create a new  FieldMatrix<T>using the input array as the underlying
 data array. | 
| Array2DRowFieldMatrix(Field<T> field,
                     T[][] d,
                     boolean copyArray)Create a new  FieldMatrix<T>using the input array as the underlying
 data array. | 
| Array2DRowFieldMatrix(T[][] d)Create a new  FieldMatrix<T>using the input array as the underlying
 data array. | 
| Array2DRowFieldMatrix(T[][] d,
                     boolean copyArray)Create a new  FieldMatrix<T>using the input array as the underlying
 data array. | 
| Array2DRowRealMatrix(double[][] d)Create a new  RealMatrixusing the input array as the underlying
 data array. | 
| Array2DRowRealMatrix(double[][] d,
                    boolean copyArray)Create a new RealMatrix using the input array as the underlying
 data array. | 
| ArrayFieldVector(ArrayFieldVector<T> v)Construct a vector from another vector, using a deep copy. | 
| ArrayFieldVector(ArrayFieldVector<T> v1,
                ArrayFieldVector<T> v2)Deprecated. 
 as of 3.2, replaced by  ArrayFieldVector.ArrayFieldVector(FieldVector, FieldVector) | 
| ArrayFieldVector(ArrayFieldVector<T> v,
                boolean deep)Construct a vector from another vector. | 
| ArrayFieldVector(ArrayFieldVector<T> v1,
                T[] v2)Deprecated. 
 as of 3.2, replaced by  ArrayFieldVector.ArrayFieldVector(FieldVector, FieldElement[]) | 
| ArrayFieldVector(Field<T> field,
                T[] d)Construct a vector from an array, copying the input array. | 
| ArrayFieldVector(Field<T> field,
                T[] d,
                boolean copyArray)Create a new ArrayFieldVector using the input array as the underlying
 data array. | 
| ArrayFieldVector(Field<T> field,
                T[] d,
                int pos,
                int size)Construct a vector from part of a array. | 
| ArrayFieldVector(Field<T> field,
                T[] v1,
                T[] v2)Construct a vector by appending one vector to another vector. | 
| ArrayFieldVector(FieldVector<T> v)Construct a vector from another vector, using a deep copy. | 
| ArrayFieldVector(FieldVector<T> v1,
                FieldVector<T> v2)Construct a vector by appending one vector to another vector. | 
| ArrayFieldVector(FieldVector<T> v1,
                T[] v2)Construct a vector by appending one vector to another vector. | 
| ArrayFieldVector(T[] d)Construct a vector from an array, copying the input array. | 
| ArrayFieldVector(T[] v1,
                ArrayFieldVector<T> v2)Deprecated. 
 as of 3.2, replaced by  ArrayFieldVector.ArrayFieldVector(FieldElement[], FieldVector) | 
| ArrayFieldVector(T[] d,
                boolean copyArray)Create a new ArrayFieldVector using the input array as the underlying
 data array. | 
| ArrayFieldVector(T[] v1,
                FieldVector<T> v2)Construct a vector by appending one vector to another vector. | 
| ArrayFieldVector(T[] d,
                int pos,
                int size)Construct a vector from part of a array. | 
| ArrayFieldVector(T[] v1,
                T[] v2)Construct a vector by appending one vector to another vector. | 
| ArrayRealVector(ArrayRealVector v)Construct a vector from another vector, using a deep copy. | 
| ArrayRealVector(double[] d,
               boolean copyArray)Create a new ArrayRealVector using the input array as the underlying
 data array. | 
| ArrayRealVector(double[] d,
               int pos,
               int size)Construct a vector from part of a array. | 
| ArrayRealVector(Double[] d,
               int pos,
               int size)Construct a vector from part of an array. | 
| ArrayRealVector(RealVector v)Construct a vector from another vector, using a deep copy. | 
| ConjugateGradient(IterationManager manager,
                 double delta,
                 boolean check)Creates a new instance of this class, with default
 stopping criterion and custom iteration manager. | 
| DiagonalMatrix(double[] d,
              boolean copyArray)Creates a matrix using the input array as the underlying data. | 
| IterativeLinearSolver(IterationManager manager)Creates a new instance of this class, with custom iteration manager. | 
| PreconditionedIterativeLinearSolver(IterationManager manager)Creates a new instance of this class, with custom iteration manager. | 
| SparseFieldVector(Field<T> field,
                 T[] values)Create from a Field array. | 
| Modifier and Type | Method and Description | 
|---|---|
| List<Cluster<T>> | DBSCANClusterer. cluster(Collection<T> points)Performs DBSCAN cluster analysis. | 
| Constructor and Description | 
|---|
| MultiStartMultivariateOptimizer(MultivariateOptimizer optimizer,
                               int starts,
                               RandomVectorGenerator generator)Create a multi-start optimizer from a single-start optimizer. | 
| Constructor and Description | 
|---|
| MultiStartMultivariateVectorOptimizer(MultivariateVectorOptimizer optimizer,
                                     int starts,
                                     RandomVectorGenerator generator)Deprecated.  Create a multi-start optimizer from a single-start optimizer. | 
| Modifier and Type | Method and Description | 
|---|---|
| void | ValueServer. computeDistribution()Computes the empirical distribution using values from the file
 in  valuesFileURL, using the default number of bins. | 
| void | ValueServer. computeDistribution(int binCount)Computes the empirical distribution using values from the file
 in  valuesFileURLandbinCountbins. | 
| void | EmpiricalDistribution. load(double[] in)Computes the empirical distribution from the provided
 array of numbers. | 
| void | EmpiricalDistribution. load(File file)Computes the empirical distribution from the input file. | 
| void | EmpiricalDistribution. load(URL url)Computes the empirical distribution using data read from a URL. | 
| Constructor and Description | 
|---|
| HaltonSequenceGenerator(int dimension,
                       int[] bases,
                       int[] weights)Construct a new Halton sequence generator with the given base numbers and weights for each dimension. | 
| StableRandomGenerator(RandomGenerator generator,
                     double alpha,
                     double beta)Create a new generator. | 
| Modifier and Type | Method and Description | 
|---|---|
| void | Frequency. merge(Collection<Frequency> others)Merge a  CollectionofFrequencyobjects into this instance. | 
| void | Frequency. merge(Frequency other)Merge another Frequency object's counts into this instance. | 
| Modifier and Type | Method and Description | 
|---|---|
| List<Cluster<T>> | DBSCANClusterer. cluster(Collection<T> points)Deprecated.  Performs DBSCAN cluster analysis. | 
| Modifier and Type | Method and Description | 
|---|---|
| static void | DescriptiveStatistics. copy(DescriptiveStatistics source,
    DescriptiveStatistics dest)Copies source to dest. | 
| static void | SummaryStatistics. copy(SummaryStatistics source,
    SummaryStatistics dest)Copies source to dest. | 
| static void | SynchronizedDescriptiveStatistics. copy(SynchronizedDescriptiveStatistics source,
    SynchronizedDescriptiveStatistics dest)Copies source to dest. | 
| static void | SynchronizedSummaryStatistics. copy(SynchronizedSummaryStatistics source,
    SynchronizedSummaryStatistics dest)Copies source to dest. | 
| Constructor and Description | 
|---|
| AggregateSummaryStatistics(SummaryStatistics prototypeStatistics)Initializes a new AggregateSummaryStatistics with the specified statistics
 object as a prototype for contributing statistics and for the internal
 aggregate statistics. | 
| DescriptiveStatistics(DescriptiveStatistics original)Copy constructor. | 
| SummaryStatistics(SummaryStatistics original)A copy constructor. | 
| SynchronizedDescriptiveStatistics(SynchronizedDescriptiveStatistics original)A copy constructor. | 
| SynchronizedSummaryStatistics(SynchronizedSummaryStatistics original)A copy constructor. | 
| Modifier and Type | Method and Description | 
|---|---|
| static void | GeometricMean. copy(GeometricMean source,
    GeometricMean dest)Copies source to dest. | 
| static void | Kurtosis. copy(Kurtosis source,
    Kurtosis dest)Copies source to dest. | 
| static void | Mean. copy(Mean source,
    Mean dest)Copies source to dest. | 
| static void | SecondMoment. copy(SecondMoment source,
    SecondMoment dest)Copies source to dest. | 
| static void | SemiVariance. copy(SemiVariance source,
    SemiVariance dest)Copies source to dest. | 
| static void | Skewness. copy(Skewness source,
    Skewness dest)Copies source to dest. | 
| static void | StandardDeviation. copy(StandardDeviation source,
    StandardDeviation dest)Copies source to dest. | 
| static void | Variance. copy(Variance source,
    Variance dest)Copies source to dest. | 
| Constructor and Description | 
|---|
| GeometricMean(GeometricMean original)Copy constructor, creates a new  GeometricMeanidentical
 to theoriginal | 
| Kurtosis(Kurtosis original)Copy constructor, creates a new  Kurtosisidentical
 to theoriginal | 
| Mean(Mean original)Copy constructor, creates a new  Meanidentical
 to theoriginal | 
| SecondMoment(SecondMoment original)Copy constructor, creates a new  SecondMomentidentical
 to theoriginal | 
| SemiVariance(SemiVariance original)Copy constructor, creates a new  SemiVarianceidentical
 to theoriginal | 
| Skewness(Skewness original)Copy constructor, creates a new  Skewnessidentical
 to theoriginal | 
| StandardDeviation(StandardDeviation original)Copy constructor, creates a new  StandardDeviationidentical
 to theoriginal | 
| Variance(Variance original)Copy constructor, creates a new  Varianceidentical
 to theoriginal | 
| Modifier and Type | Method and Description | 
|---|---|
| static void | Max. copy(Max source,
    Max dest)Copies source to dest. | 
| static void | Min. copy(Min source,
    Min dest)Copies source to dest. | 
| Constructor and Description | 
|---|
| Max(Max original)Copy constructor, creates a new  Maxidentical
 to theoriginal | 
| Median(Median original)Copy constructor, creates a new  Medianidentical
 to theoriginal | 
| Min(Min original)Copy constructor, creates a new  Minidentical
 to theoriginal | 
| Percentile(Percentile original)Copy constructor, creates a new  Percentileidentical
 to theoriginal | 
| Modifier and Type | Method and Description | 
|---|---|
| static void | Product. copy(Product source,
    Product dest)Copies source to dest. | 
| static void | SumOfLogs. copy(SumOfLogs source,
    SumOfLogs dest)Copies source to dest. | 
| static void | SumOfSquares. copy(SumOfSquares source,
    SumOfSquares dest)Copies source to dest. | 
| static void | Sum. copy(Sum source,
    Sum dest)Copies source to dest. | 
| Constructor and Description | 
|---|
| Product(Product original)Copy constructor, creates a new  Productidentical
 to theoriginal | 
| Sum(Sum original)Copy constructor, creates a new  Sumidentical
 to theoriginal | 
| SumOfLogs(SumOfLogs original)Copy constructor, creates a new  SumOfLogsidentical
 to theoriginal | 
| SumOfSquares(SumOfSquares original)Copy constructor, creates a new  SumOfSquaresidentical
 to theoriginal | 
| Modifier and Type | Method and Description | 
|---|---|
| double | OneWayAnova. anovaFValue(Collection<double[]> categoryData)Computes the ANOVA F-value for a collection of  double[]arrays. | 
| double | OneWayAnova. anovaPValue(Collection<double[]> categoryData)Computes the ANOVA P-value for a collection of  double[]arrays. | 
| double | OneWayAnova. anovaPValue(Collection<SummaryStatistics> categoryData,
           boolean allowOneElementData)Computes the ANOVA P-value for a collection of  SummaryStatistics. | 
| boolean | OneWayAnova. anovaTest(Collection<double[]> categoryData,
         double alpha)Performs an ANOVA test, evaluating the null hypothesis that there
 is no difference among the means of the data categories. | 
| static double | TestUtils. chiSquare(long[][] counts) | 
| double | ChiSquareTest. chiSquare(long[][] counts)Computes the Chi-Square statistic associated with a
 
  chi-square test of independence based on the input  countsarray, viewed as a two-way table. | 
| static double | TestUtils. chiSquareTest(long[][] counts) | 
| double | ChiSquareTest. chiSquareTest(long[][] counts)Returns the observed significance level, or 
 p-value, associated with a
 
 chi-square test of independence based on the input  countsarray, viewed as a two-way table. | 
| static boolean | TestUtils. chiSquareTest(long[][] counts,
             double alpha) | 
| boolean | ChiSquareTest. chiSquareTest(long[][] counts,
             double alpha)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. | 
| static double | TestUtils. homoscedasticT(double[] sample1,
              double[] sample2) | 
| double | TTest. homoscedasticT(double[] sample1,
              double[] sample2)Computes a 2-sample t statistic,  under the hypothesis of equal
 subpopulation variances. | 
| static double | TestUtils. homoscedasticT(StatisticalSummary sampleStats1,
              StatisticalSummary sampleStats2) | 
| double | TTest. homoscedasticT(StatisticalSummary sampleStats1,
              StatisticalSummary sampleStats2)Computes a 2-sample t statistic, comparing the means of the datasets
 described by two  StatisticalSummaryinstances, under the
 assumption of equal subpopulation variances. | 
| static double | TestUtils. homoscedasticTTest(double[] sample1,
                  double[] sample2) | 
| double | TTest. homoscedasticTTest(double[] sample1,
                  double[] sample2)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. | 
| static boolean | TestUtils. homoscedasticTTest(double[] sample1,
                  double[] sample2,
                  double alpha) | 
| boolean | TTest. homoscedasticTTest(double[] sample1,
                  double[] sample2,
                  double alpha)Performs a
 
 two-sided t-test evaluating the null hypothesis that  sample1andsample2are drawn from populations with the same mean,
 with significance levelalpha,  assuming that the
 subpopulation variances are equal. | 
| static double | TestUtils. homoscedasticTTest(StatisticalSummary sampleStats1,
                  StatisticalSummary sampleStats2) | 
| double | TTest. homoscedasticTTest(StatisticalSummary sampleStats1,
                  StatisticalSummary sampleStats2)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. | 
| static double | TestUtils. kolmogorovSmirnovStatistic(double[] x,
                          double[] y) | 
| static double | TestUtils. kolmogorovSmirnovStatistic(RealDistribution dist,
                          double[] data) | 
| static double | TestUtils. kolmogorovSmirnovTest(double[] x,
                     double[] y) | 
| static double | TestUtils. kolmogorovSmirnovTest(double[] x,
                     double[] y,
                     boolean strict) | 
| static double | TestUtils. kolmogorovSmirnovTest(RealDistribution dist,
                     double[] data) | 
| static double | TestUtils. kolmogorovSmirnovTest(RealDistribution dist,
                     double[] data,
                     boolean strict) | 
| static boolean | TestUtils. kolmogorovSmirnovTest(RealDistribution dist,
                     double[] data,
                     double alpha) | 
| double | MannWhitneyUTest. mannWhitneyU(double[] x,
            double[] y)Computes the  Mann-Whitney
 U statistic comparing mean for two independent samples possibly of
 different length. | 
| double | MannWhitneyUTest. mannWhitneyUTest(double[] x,
                double[] y)Returns the asymptotic observed significance level, or 
 p-value, associated with a  Mann-Whitney
 U statistic comparing mean for two independent samples. | 
| static double | TestUtils. oneWayAnovaFValue(Collection<double[]> categoryData) | 
| static double | TestUtils. oneWayAnovaPValue(Collection<double[]> categoryData) | 
| static boolean | TestUtils. oneWayAnovaTest(Collection<double[]> categoryData,
               double alpha) | 
| static double | TestUtils. pairedT(double[] sample1,
       double[] sample2) | 
| double | TTest. pairedT(double[] sample1,
       double[] sample2)Computes a paired, 2-sample t-statistic based on the data in the input
 arrays. | 
| static double | TestUtils. pairedTTest(double[] sample1,
           double[] sample2) | 
| double | TTest. pairedTTest(double[] sample1,
           double[] sample2)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. | 
| static boolean | TestUtils. pairedTTest(double[] sample1,
           double[] sample2,
           double alpha) | 
| boolean | TTest. pairedTTest(double[] sample1,
           double[] sample2,
           double alpha)Performs a paired t-test evaluating the null hypothesis that the
 mean of the paired differences between  sample1andsample2is 0 in favor of the two-sided alternative that the
 mean paired difference is not equal to 0, with significance levelalpha. | 
| static double | TestUtils. t(double[] sample1,
 double[] sample2) | 
| double | TTest. t(double[] sample1,
 double[] sample2)Computes a 2-sample t statistic, without the hypothesis of equal
 subpopulation variances. | 
| static double | TestUtils. t(double mu,
 double[] observed) | 
| double | TTest. t(double mu,
 double[] observed)Computes a 
 t statistic  given observed values and a comparison constant. | 
| static double | TestUtils. t(double mu,
 StatisticalSummary sampleStats) | 
| double | TTest. t(double mu,
 StatisticalSummary sampleStats) | 
| static double | TestUtils. t(StatisticalSummary sampleStats1,
 StatisticalSummary sampleStats2) | 
| double | TTest. t(StatisticalSummary sampleStats1,
 StatisticalSummary sampleStats2)Computes a 2-sample t statistic , comparing the means of the datasets
 described by two  StatisticalSummaryinstances, without the
 assumption of equal subpopulation variances. | 
| static double | TestUtils. tTest(double[] sample1,
     double[] sample2) | 
| double | TTest. tTest(double[] sample1,
     double[] sample2)Returns the observed significance level, or
 p-value, associated with a two-sample, two-tailed t-test
 comparing the means of the input arrays. | 
| static boolean | TestUtils. tTest(double[] sample1,
     double[] sample2,
     double alpha) | 
| boolean | TTest. tTest(double[] sample1,
     double[] sample2,
     double alpha)Performs a
 
 two-sided t-test evaluating the null hypothesis that  sample1andsample2are drawn from populations with the same mean,
 with significance levelalpha. | 
| static double | TestUtils. tTest(double mu,
     double[] sample) | 
| double | TTest. tTest(double mu,
     double[] sample)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. | 
| static boolean | TestUtils. tTest(double mu,
     double[] sample,
     double alpha) | 
| boolean | TTest. tTest(double mu,
     double[] sample,
     double alpha)Performs a 
 two-sided t-test evaluating the null hypothesis that the mean of the population from
 which  sampleis drawn equalsmu. | 
| static double | TestUtils. tTest(double mu,
     StatisticalSummary sampleStats) | 
| double | TTest. tTest(double mu,
     StatisticalSummary sampleStats)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  sampleStatswith the constantmu. | 
| static boolean | TestUtils. tTest(double mu,
     StatisticalSummary sampleStats,
     double alpha) | 
| boolean | TTest. tTest(double mu,
     StatisticalSummary sampleStats,
     double alpha)Performs a 
 two-sided t-test evaluating the null hypothesis that the mean of the
 population from which the dataset described by  statsis
 drawn equalsmu. | 
| static double | TestUtils. tTest(StatisticalSummary sampleStats1,
     StatisticalSummary sampleStats2) | 
| double | TTest. tTest(StatisticalSummary sampleStats1,
     StatisticalSummary sampleStats2)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. | 
| static boolean | TestUtils. tTest(StatisticalSummary sampleStats1,
     StatisticalSummary sampleStats2,
     double alpha) | 
| boolean | TTest. tTest(StatisticalSummary sampleStats1,
     StatisticalSummary sampleStats2,
     double alpha)Performs a
 
 two-sided t-test evaluating the null hypothesis that
  sampleStats1andsampleStats2describe
 datasets drawn from populations with the same mean, with significance
 levelalpha. | 
| double | WilcoxonSignedRankTest. wilcoxonSignedRank(double[] x,
                  double[] y)Computes the 
 Wilcoxon signed ranked statistic comparing mean for two related
 samples or repeated measurements on a single sample. | 
| double | WilcoxonSignedRankTest. wilcoxonSignedRankTest(double[] x,
                      double[] y,
                      boolean exactPValue)Returns the observed significance level, or 
 p-value, associated with a 
 Wilcoxon signed ranked statistic comparing mean for two related
 samples or repeated measurements on a single sample. | 
| Modifier and Type | Method and Description | 
|---|---|
| static void | MathUtils. checkNotNull(Object o)Checks that an object is not null. | 
| static void | MathUtils. checkNotNull(Object o,
            Localizable pattern,
            Object... args)Checks that an object is not null. | 
| static void | MathArrays. checkRectangular(long[][] in)Throws DimensionMismatchException if the input array is not rectangular. | 
| static double[] | MathArrays. convolve(double[] x,
        double[] h)Calculates the 
 convolution between two sequences. | 
| static void | ResizableDoubleArray. copy(ResizableDoubleArray source,
    ResizableDoubleArray dest)Copies source to dest, copying the underlying data, so dest is
 a new, independent copy of source. | 
| static void | MathArrays. sortInPlace(double[] x,
           double[]... yList)Sort an array in ascending order in place and perform the same reordering
 of entries on other arrays. | 
| static void | MathArrays. sortInPlace(double[] x,
           MathArrays.OrderDirection dir,
           double[]... yList)Sort an array in place and perform the same reordering of entries on
 other arrays. | 
| double | DefaultTransformer. transform(Object o) | 
| Constructor and Description | 
|---|
| Incrementor(int max,
           Incrementor.MaxCountExceededCallback cb)Deprecated.  Defines a maximal count and a callback method to be triggered at
 counter exhaustion. | 
| KthSelector(PivotingStrategyInterface pivotingStrategy)Constructor with specified pivoting strategy | 
| ResizableDoubleArray(ResizableDoubleArray original)Copy constructor. | 
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