## Uses of Class
org.apache.commons.math3.exception.NumberIsTooSmallException

- Packages that use NumberIsTooSmallException
  Package | Description
  --- | ---
  org.apache.commons.math3.analysis.differentiation | This package holds the main interfaces and basic building block classes dealing with differentiation.
  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.dfp | Decimal floating point library for Java
  org.apache.commons.math3.distribution | Implementations of common discrete and continuous distributions.
  org.apache.commons.math3.distribution.fitting | Fitting of parameters against distributions.
  org.apache.commons.math3.exception | Specialized exceptions for algorithms errors.
  org.apache.commons.math3.genetics | This package provides Genetic Algorithms components and implementations.
  org.apache.commons.math3.linear | Linear algebra support.
  org.apache.commons.math3.ml.clustering | Clustering algorithms.
  org.apache.commons.math3.ode | This package provides classes to solve Ordinary Differential Equations problems.
  org.apache.commons.math3.ode.nonstiff | This package provides classes to solve non-stiff Ordinary Differential Equations problems.
  org.apache.commons.math3.special | Implementations of special functions such as Beta and Gamma.
  org.apache.commons.math3.stat | Data storage, manipulation and summary routines.
  org.apache.commons.math3.stat.correlation | Correlations/Covariance computations.
  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.

- - ### Uses of NumberIsTooSmallException in org.apache.commons.math3.analysis.differentiation

    Constructors in org.apache.commons.math3.analysis.differentiation that throw NumberIsTooSmallException
    Constructor and Description
    `FiniteDifferencesDifferentiator(int nbPoints, double stepSize)` Build a differentiator with number of points and step size when independent variable is unbounded.
    `FiniteDifferencesDifferentiator(int nbPoints, double stepSize, double tLower, double tUpper)` Build a differentiator with number of points and step size when independent variable is bounded.

  - ### Uses of NumberIsTooSmallException in org.apache.commons.math3.analysis.integration

    Constructors in org.apache.commons.math3.analysis.integration that throw NumberIsTooSmallException
    Constructor and Description
    `BaseAbstractUnivariateIntegrator(double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)` Construct an integrator with given accuracies and iteration counts.
    `BaseAbstractUnivariateIntegrator(int minimalIterationCount, int maximalIterationCount)` Construct an integrator with given iteration counts.
    `IterativeLegendreGaussIntegrator(int n, double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)` Builds an integrator with given accuracies and iterations counts.
    `IterativeLegendreGaussIntegrator(int n, int minimalIterationCount, int maximalIterationCount)` Builds an integrator with given iteration counts.
    `LegendreGaussIntegrator(int n, double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)` Deprecated. Build a Legendre-Gauss integrator with given accuracies and iterations counts.
    `MidPointIntegrator(double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)` Build a midpoint integrator with given accuracies and iterations counts.
    `MidPointIntegrator(int minimalIterationCount, int maximalIterationCount)` Build a midpoint integrator with given iteration counts.
    `RombergIntegrator(double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)` Build a Romberg integrator with given accuracies and iterations counts.
    `RombergIntegrator(int minimalIterationCount, int maximalIterationCount)` Build a Romberg integrator with given iteration counts.
    `SimpsonIntegrator(double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)` Build a Simpson integrator with given accuracies and iterations counts.
    `SimpsonIntegrator(int minimalIterationCount, int maximalIterationCount)` Build a Simpson integrator with given iteration counts.
    `TrapezoidIntegrator(double relativeAccuracy, double absoluteAccuracy, int minimalIterationCount, int maximalIterationCount)` Build a trapezoid integrator with given accuracies and iterations counts.
    `TrapezoidIntegrator(int minimalIterationCount, int maximalIterationCount)` Build a trapezoid integrator with given iteration counts.

  - ### Uses of NumberIsTooSmallException in org.apache.commons.math3.analysis.interpolation

    Methods in org.apache.commons.math3.analysis.interpolation that throw NumberIsTooSmallException
    Modifier and Type | Method and Description
    --- | ---
    `protected static double[]` | DividedDifferenceInterpolator.`computeDividedDifference(double[] x, double[] y)` Return a copy of the divided difference array.
    `UnivariateFunction` | UnivariatePeriodicInterpolator.`interpolate(double[] xval, double[] yval)` Compute an interpolating function for the dataset.
    `PolynomialSplineFunction` | LinearInterpolator.`interpolate(double[] x, double[] y)` Computes a linear interpolating function for the data set.
    `PolynomialFunctionLagrangeForm` | NevilleInterpolator.`interpolate(double[] x, double[] y)` Computes an interpolating function for the data set.
    `PolynomialSplineFunction` | AkimaSplineInterpolator.`interpolate(double[] xvals, double[] yvals)` Computes an interpolating function for the data set.
    `PolynomialSplineFunction` | SplineInterpolator.`interpolate(double[] x, double[] y)` Computes an interpolating function for the data set.
    `PolynomialFunctionNewtonForm` | DividedDifferenceInterpolator.`interpolate(double[] x, double[] y)` Compute an interpolating function for the dataset.
    `PolynomialSplineFunction` | LoessInterpolator.`interpolate(double[] xval, double[] yval)` Compute an interpolating function by performing a loess fit on the data at the original abscissae and then building a cubic spline with a `SplineInterpolator` on the resulting fit.
    `BicubicInterpolatingFunction` | BicubicInterpolator.`interpolate(double[] xval, double[] yval, double[][] fval)` Compute an interpolating function for the dataset.
    `BicubicSplineInterpolatingFunction` | BicubicSplineInterpolator.`interpolate(double[] xval, double[] yval, double[][] fval)` Deprecated. Compute an interpolating function for the dataset.
    `BivariateFunction` | BivariateGridInterpolator.`interpolate(double[] xval, double[] yval, double[][] fval)` Compute an interpolating function for the dataset.
    `TricubicInterpolatingFunction` | TricubicInterpolator.`interpolate(double[] xval, double[] yval, double[] zval, double[][][] fval)` Compute an interpolating function for the dataset.
    `TrivariateFunction` | TrivariateGridInterpolator.`interpolate(double[] xval, double[] yval, double[] zval, double[][][] fval)` Compute an interpolating function for the dataset.
    `TricubicSplineInterpolatingFunction` | TricubicSplineInterpolator.`interpolate(double[] xval, double[] yval, double[] zval, double[][][] fval)` Deprecated. Compute an interpolating function for the dataset.
    `double[]` | LoessInterpolator.`smooth(double[] xval, double[] yval)` Compute a loess fit on the data at the original abscissae.
    `double[]` | LoessInterpolator.`smooth(double[] xval, double[] yval, double[] weights)` Compute a weighted loess fit on the data at the original abscissae.

  - ### Uses of NumberIsTooSmallException in org.apache.commons.math3.analysis.polynomials

    Methods in org.apache.commons.math3.analysis.polynomials that throw NumberIsTooSmallException
    Modifier and Type | Method and Description
    --- | ---
    `static double` | PolynomialFunctionLagrangeForm.`evaluate(double[] x, double[] y, double z)` Evaluate the Lagrange polynomial using Neville's Algorithm.
    `static boolean` | PolynomialFunctionLagrangeForm.`verifyInterpolationArray(double[] x, double[] y, boolean abort)` Check that the interpolation arrays are valid.

    Constructors in org.apache.commons.math3.analysis.polynomials that throw NumberIsTooSmallException
    Constructor and Description
    `PolynomialFunctionLagrangeForm(double[] x, double[] y)` Construct a Lagrange polynomial with the given abscissas and function values.
    `PolynomialSplineFunction(double[] knots, PolynomialFunction[] polynomials)` Construct a polynomial spline function with the given segment delimiters and interpolating polynomials.

  - ### Uses of NumberIsTooSmallException in org.apache.commons.math3.analysis.solvers

    Constructors in org.apache.commons.math3.analysis.solvers that throw NumberIsTooSmallException
    Constructor and Description
    `BracketingNthOrderBrentSolver(double relativeAccuracy, double absoluteAccuracy, double functionValueAccuracy, int maximalOrder)` Construct a solver.
    `BracketingNthOrderBrentSolver(double relativeAccuracy, double absoluteAccuracy, int maximalOrder)` Construct a solver.
    `BracketingNthOrderBrentSolver(double absoluteAccuracy, int maximalOrder)` Construct a solver.
    `FieldBracketingNthOrderBrentSolver(T relativeAccuracy, T absoluteAccuracy, T functionValueAccuracy, int maximalOrder)` Construct a solver.

  - ### Uses of NumberIsTooSmallException in org.apache.commons.math3.dfp

    Constructors in org.apache.commons.math3.dfp that throw NumberIsTooSmallException
    Constructor and Description
    `BracketingNthOrderBrentSolverDFP(Dfp relativeAccuracy, Dfp absoluteAccuracy, Dfp functionValueAccuracy, int maximalOrder)` Deprecated. Construct a solver.

  - ### Uses of NumberIsTooSmallException in org.apache.commons.math3.distribution

    Constructors in org.apache.commons.math3.distribution that throw NumberIsTooSmallException
    Constructor and Description
    `TriangularDistribution(double a, double c, double b)` Creates a triangular real distribution using the given lower limit, upper limit, and mode.
    `TriangularDistribution(RandomGenerator rng, double a, double c, double b)` Creates a triangular distribution.

  - ### Uses of NumberIsTooSmallException in org.apache.commons.math3.distribution.fitting

    Constructors in org.apache.commons.math3.distribution.fitting that throw NumberIsTooSmallException
    Constructor and Description
    `MultivariateNormalMixtureExpectationMaximization(double[][] data)` Creates an object to fit a multivariate normal mixture model to data.

  - ### Uses of NumberIsTooSmallException in org.apache.commons.math3.exception

    Subclasses of NumberIsTooSmallException in org.apache.commons.math3.exception
    Modifier and Type | Class and Description
    --- | ---
    `class` | `NotPositiveException` Exception to be thrown when the argument is negative.
    `class` | `NotStrictlyPositiveException` Exception to be thrown when the argument is not greater than 0.

  - ### Uses of NumberIsTooSmallException in org.apache.commons.math3.genetics

    Methods in org.apache.commons.math3.genetics that throw NumberIsTooSmallException
    Modifier and Type | Method and Description
    --- | ---
    `void` | ListPopulation.`setPopulationLimit(int populationLimit)` Sets the maximal population size.

    Constructors in org.apache.commons.math3.genetics that throw NumberIsTooSmallException
    Constructor and Description
    `FixedElapsedTime(long maxTime)` Create a new `FixedElapsedTime` instance.
    `FixedElapsedTime(long maxTime, TimeUnit unit)` Create a new `FixedElapsedTime` instance.
    `FixedGenerationCount(int maxGenerations)` Create a new FixedGenerationCount instance.

  - ### Uses of NumberIsTooSmallException in org.apache.commons.math3.linear

    Subclasses of NumberIsTooSmallException in org.apache.commons.math3.linear
    Modifier and Type | Class and Description
    --- | ---
    `class` | `NonPositiveDefiniteMatrixException` Exception to be thrown when a positive definite matrix is expected.

    Methods in org.apache.commons.math3.linear that throw NumberIsTooSmallException
    Modifier and Type | Method and Description
    --- | ---
    `protected void` | RealVector.`checkIndices(int start, int end)` Checks that the indices of a subvector are valid.
    `static void` | MatrixUtils.`checkSubMatrixIndex(AnyMatrix m, int startRow, int endRow, int startColumn, int endColumn)` Check if submatrix ranges indices are valid.
    `protected void` | AbstractFieldMatrix.`checkSubMatrixIndex(int startRow, int endRow, int startColumn, int endColumn)` Check if submatrix ranges indices are valid.
    `void` | AbstractRealMatrix.`copySubMatrix(int startRow, int endRow, int startColumn, int endColumn, double[][] destination)` Copy a submatrix.
    `void` | RealMatrix.`copySubMatrix(int startRow, int endRow, int startColumn, int endColumn, double[][] destination)` Copy a submatrix.
    `void` | AbstractFieldMatrix.`copySubMatrix(int startRow, int endRow, int startColumn, int endColumn, T[][] destination)` Copy a submatrix.
    `void` | FieldMatrix.`copySubMatrix(int startRow, int endRow, int startColumn, int endColumn, T[][] destination)` Copy a submatrix.
    `BlockRealMatrix` | BlockRealMatrix.`getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)` Gets a submatrix.
    `RealMatrix` | AbstractRealMatrix.`getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)` Gets a submatrix.
    `FieldMatrix<T>` | AbstractFieldMatrix.`getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)` Get a submatrix.
    `RealMatrix` | RealMatrix.`getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)` Gets a submatrix.
    `FieldMatrix<T>` | BlockFieldMatrix.`getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)` Get a submatrix.
    `FieldMatrix<T>` | FieldMatrix.`getSubMatrix(int startRow, int endRow, int startColumn, int endColumn)` Get a submatrix.
    `T` | Array2DRowFieldMatrix.`walkInColumnOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in column order.
    `T` | AbstractFieldMatrix.`walkInColumnOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in column order.
    `T` | FieldMatrix.`walkInColumnOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in column order.
    `T` | Array2DRowFieldMatrix.`walkInColumnOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in column order.
    `T` | AbstractFieldMatrix.`walkInColumnOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in column order.
    `T` | FieldMatrix.`walkInColumnOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in column order.
    `double` | AbstractRealMatrix.`walkInColumnOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in column order.
    `double` | RealMatrix.`walkInColumnOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in column order.
    `double` | Array2DRowRealMatrix.`walkInColumnOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in column order.
    `double` | AbstractRealMatrix.`walkInColumnOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in column order.
    `double` | RealMatrix.`walkInColumnOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in column order.
    `double` | Array2DRowRealMatrix.`walkInColumnOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in column order.
    `T` | SparseFieldVector.`walkInDefaultOrder(FieldVectorChangingVisitor<T> visitor, int start, int end)` Visits (and possibly alters) some entries of this vector in default order (increasing index).
    `T` | ArrayFieldVector.`walkInDefaultOrder(FieldVectorChangingVisitor<T> visitor, int start, int end)` Visits (and possibly alters) some entries of this vector in default order (increasing index).
    `T` | SparseFieldVector.`walkInDefaultOrder(FieldVectorPreservingVisitor<T> visitor, int start, int end)` Visits (but does not alter) some entries of this vector in default order (increasing index).
    `T` | ArrayFieldVector.`walkInDefaultOrder(FieldVectorPreservingVisitor<T> visitor, int start, int end)` Visits (but does not alter) some entries of this vector in default order (increasing index).
    `double` | RealVector.`walkInDefaultOrder(RealVectorChangingVisitor visitor, int start, int end)` Visits (and possibly alters) some entries of this vector in default order (increasing index).
    `double` | ArrayRealVector.`walkInDefaultOrder(RealVectorChangingVisitor visitor, int start, int end)` Visits (and possibly alters) some entries of this vector in default order (increasing index).
    `double` | RealVector.`walkInDefaultOrder(RealVectorPreservingVisitor visitor, int start, int end)` Visits (but does not alter) some entries of this vector in default order (increasing index).
    `double` | ArrayRealVector.`walkInDefaultOrder(RealVectorPreservingVisitor visitor, int start, int end)` Visits (but does not alter) some entries of this vector in default order (increasing index).
    `T` | AbstractFieldMatrix.`walkInOptimizedOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries using the fastest possible order.
    `T` | BlockFieldMatrix.`walkInOptimizedOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries using the fastest possible order.
    `T` | FieldMatrix.`walkInOptimizedOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries using the fastest possible order.
    `T` | AbstractFieldMatrix.`walkInOptimizedOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries using the fastest possible order.
    `T` | BlockFieldMatrix.`walkInOptimizedOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries using the fastest possible order.
    `T` | FieldMatrix.`walkInOptimizedOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries using the fastest possible order.
    `T` | SparseFieldVector.`walkInOptimizedOrder(FieldVectorChangingVisitor<T> visitor, int start, int end)` Visits (and possibly change) some entries of this vector in optimized order.
    `T` | ArrayFieldVector.`walkInOptimizedOrder(FieldVectorChangingVisitor<T> visitor, int start, int end)` Visits (and possibly change) some entries of this vector in optimized order.
    `T` | SparseFieldVector.`walkInOptimizedOrder(FieldVectorPreservingVisitor<T> visitor, int start, int end)` Visits (but does not alter) some entries of this vector in optimized order.
    `T` | ArrayFieldVector.`walkInOptimizedOrder(FieldVectorPreservingVisitor<T> visitor, int start, int end)` Visits (but does not alter) some entries of this vector in optimized order.
    `double` | BlockRealMatrix.`walkInOptimizedOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries using the fastest possible order.
    `double` | AbstractRealMatrix.`walkInOptimizedOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries using the fastest possible order.
    `double` | RealMatrix.`walkInOptimizedOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries using the fastest possible order.
    `double` | BlockRealMatrix.`walkInOptimizedOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries using the fastest possible order.
    `double` | AbstractRealMatrix.`walkInOptimizedOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries using the fastest possible order.
    `double` | RealMatrix.`walkInOptimizedOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries using the fastest possible order.
    `double` | RealVector.`walkInOptimizedOrder(RealVectorChangingVisitor visitor, int start, int end)` Visits (and possibly change) some entries of this vector in optimized order.
    `double` | ArrayRealVector.`walkInOptimizedOrder(RealVectorChangingVisitor visitor, int start, int end)` Visits (and possibly change) some entries of this vector in optimized order.
    `double` | RealVector.`walkInOptimizedOrder(RealVectorPreservingVisitor visitor, int start, int end)` Visits (but does not alter) some entries of this vector in optimized order.
    `double` | ArrayRealVector.`walkInOptimizedOrder(RealVectorPreservingVisitor visitor, int start, int end)` Visits (but does not alter) some entries of this vector in optimized order.
    `T` | Array2DRowFieldMatrix.`walkInRowOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in row order.
    `T` | AbstractFieldMatrix.`walkInRowOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in row order.
    `T` | BlockFieldMatrix.`walkInRowOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in row order.
    `T` | FieldMatrix.`walkInRowOrder(FieldMatrixChangingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in row order.
    `T` | Array2DRowFieldMatrix.`walkInRowOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in row order.
    `T` | AbstractFieldMatrix.`walkInRowOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in row order.
    `T` | BlockFieldMatrix.`walkInRowOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in row order.
    `T` | FieldMatrix.`walkInRowOrder(FieldMatrixPreservingVisitor<T> visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in row order.
    `double` | BlockRealMatrix.`walkInRowOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in row order.
    `double` | AbstractRealMatrix.`walkInRowOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in row order.
    `double` | RealMatrix.`walkInRowOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in row order.
    `double` | Array2DRowRealMatrix.`walkInRowOrder(RealMatrixChangingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (and possibly change) some matrix entries in row order.
    `double` | BlockRealMatrix.`walkInRowOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in row order.
    `double` | AbstractRealMatrix.`walkInRowOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in row order.
    `double` | RealMatrix.`walkInRowOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in row order.
    `double` | Array2DRowRealMatrix.`walkInRowOrder(RealMatrixPreservingVisitor visitor, int startRow, int endRow, int startColumn, int endColumn)` Visit (but don't change) some matrix entries in row order.

  - ### Uses of NumberIsTooSmallException in org.apache.commons.math3.ml.clustering

    Constructors in org.apache.commons.math3.ml.clustering that throw NumberIsTooSmallException
    Constructor and Description
    `FuzzyKMeansClusterer(int k, double fuzziness)` Creates a new instance of a FuzzyKMeansClusterer.
    `FuzzyKMeansClusterer(int k, double fuzziness, int maxIterations, DistanceMeasure measure)` Creates a new instance of a FuzzyKMeansClusterer.
    `FuzzyKMeansClusterer(int k, double fuzziness, int maxIterations, DistanceMeasure measure, double epsilon, RandomGenerator random)` Creates a new instance of a FuzzyKMeansClusterer.

  - ### Uses of NumberIsTooSmallException in org.apache.commons.math3.ode

    Methods in org.apache.commons.math3.ode that throw NumberIsTooSmallException
    Modifier and Type | Method and Description
    --- | ---
    `abstract void` | AbstractIntegrator.`integrate(ExpandableStatefulODE equations, double t)` Integrate a set of differential equations up to the given time.
    `FieldODEStateAndDerivative<T>` | FirstOrderFieldIntegrator.`integrate(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime)` Integrate the differential equations up to the given time.
    `double` | FirstOrderIntegrator.`integrate(FirstOrderDifferentialEquations equations, double t0, double[] y0, double t, double[] y)` Integrate the differential equations up to the given time.
    `double` | AbstractIntegrator.`integrate(FirstOrderDifferentialEquations equations, double t0, double[] y0, double t, double[] y)` Integrate the differential equations up to the given time.
    `protected void` | AbstractIntegrator.`sanityChecks(ExpandableStatefulODE equations, double t)` Check the integration span.
    `protected void` | AbstractFieldIntegrator.`sanityChecks(FieldODEState<T> eqn, T t)` Check the integration span.
    `protected void` | MultistepIntegrator.`start(double t0, double[] y0, double t)` Start the integration.
    `protected void` | MultistepFieldIntegrator.`start(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T t)` Start the integration.

    Constructors in org.apache.commons.math3.ode that throw NumberIsTooSmallException
    Constructor and Description
    `MultistepFieldIntegrator(Field<T> field, String name, int nSteps, int order, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance)` Build a multistep integrator with the given stepsize bounds.
    `MultistepIntegrator(String name, int nSteps, int order, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance)` Build a multistep integrator with the given stepsize bounds.

  - ### Uses of NumberIsTooSmallException in org.apache.commons.math3.ode.nonstiff

    Methods in org.apache.commons.math3.ode.nonstiff that throw NumberIsTooSmallException
    Modifier and Type | Method and Description
    --- | ---
    `protected double` | AdaptiveStepsizeIntegrator.`filterStep(double h, boolean forward, boolean acceptSmall)` Filter the integration step.
    `protected T` | AdaptiveStepsizeFieldIntegrator.`filterStep(T h, boolean forward, boolean acceptSmall)` Filter the integration step.
    `abstract void` | AdamsIntegrator.`integrate(ExpandableStatefulODE equations, double t)` Integrate a set of differential equations up to the given time.
    `abstract void` | AdaptiveStepsizeIntegrator.`integrate(ExpandableStatefulODE equations, double t)` Integrate a set of differential equations up to the given time.
    `void` | AdamsMoultonIntegrator.`integrate(ExpandableStatefulODE equations, double t)` Integrate a set of differential equations up to the given time.
    `void` | EmbeddedRungeKuttaIntegrator.`integrate(ExpandableStatefulODE equations, double t)` Integrate a set of differential equations up to the given time.
    `void` | AdamsBashforthIntegrator.`integrate(ExpandableStatefulODE equations, double t)` Integrate a set of differential equations up to the given time.
    `void` | RungeKuttaIntegrator.`integrate(ExpandableStatefulODE equations, double t)` Integrate a set of differential equations up to the given time.
    `void` | GraggBulirschStoerIntegrator.`integrate(ExpandableStatefulODE equations, double t)` Integrate a set of differential equations up to the given time.
    `FieldODEStateAndDerivative<T>` | RungeKuttaFieldIntegrator.`integrate(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime)` Integrate the differential equations up to the given time.
    `FieldODEStateAndDerivative<T>` | EmbeddedRungeKuttaFieldIntegrator.`integrate(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime)` Integrate the differential equations up to the given time.
    `FieldODEStateAndDerivative<T>` | AdamsBashforthFieldIntegrator.`integrate(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime)` Integrate the differential equations up to the given time.
    `FieldODEStateAndDerivative<T>` | AdamsMoultonFieldIntegrator.`integrate(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime)` Integrate the differential equations up to the given time.
    `abstract FieldODEStateAndDerivative<T>` | AdamsFieldIntegrator.`integrate(FieldExpandableODE<T> equations, FieldODEState<T> initialState, T finalTime)` Integrate the differential equations up to the given time.
    `protected void` | AdaptiveStepsizeIntegrator.`sanityChecks(ExpandableStatefulODE equations, double t)` Check the integration span.
    `protected void` | AdaptiveStepsizeFieldIntegrator.`sanityChecks(FieldODEState<T> eqn, T t)` Check the integration span.

    Constructors in org.apache.commons.math3.ode.nonstiff that throw NumberIsTooSmallException
    Constructor and Description
    `AdamsBashforthFieldIntegrator(Field<T> field, int nSteps, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance)` Build an Adams-Bashforth integrator with the given order and step control parameters.
    `AdamsBashforthIntegrator(int nSteps, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance)` Build an Adams-Bashforth integrator with the given order and step control parameters.
    `AdamsFieldIntegrator(Field<T> field, String name, int nSteps, int order, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance)` Build an Adams integrator with the given order and step control parameters.
    `AdamsIntegrator(String name, int nSteps, int order, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance)` Build an Adams integrator with the given order and step control parameters.
    `AdamsMoultonFieldIntegrator(Field<T> field, int nSteps, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance)` Build an Adams-Moulton integrator with the given order and error control parameters.
    `AdamsMoultonIntegrator(int nSteps, double minStep, double maxStep, double scalAbsoluteTolerance, double scalRelativeTolerance)` Build an Adams-Moulton integrator with the given order and error control parameters.

  - ### Uses of NumberIsTooSmallException in org.apache.commons.math3.special

    Methods in org.apache.commons.math3.special that throw NumberIsTooSmallException
    Modifier and Type | Method and Description
    --- | ---
    `static double` | Gamma.`logGamma1p(double x)` Returns the value of log Γ(1 + x) for -0.5 ≤ x ≤ 1.5.

  - ### Uses of NumberIsTooSmallException in org.apache.commons.math3.stat

    Methods in org.apache.commons.math3.stat that throw NumberIsTooSmallException
    Modifier and Type | Method and Description
    --- | ---
    `static double` | StatUtils.`varianceDifference(double[] sample1, double[] sample2, double meanDifference)` Returns the variance of the (signed) differences between corresponding elements of the input arrays -- i.e., var(sample1[i] - sample2[i]).

  - ### Uses of NumberIsTooSmallException in org.apache.commons.math3.stat.correlation

    Methods in org.apache.commons.math3.stat.correlation that throw NumberIsTooSmallException
    Modifier and Type | Method and Description
    --- | ---
    `double` | StorelessCovariance.`getCovariance(int xIndex, int yIndex)` Get the covariance for an individual element of the covariance matrix.
    `RealMatrix` | StorelessCovariance.`getCovarianceMatrix()` Returns the covariance matrix
    `double[][]` | StorelessCovariance.`getData()` Return the covariance matrix as two-dimensional array.

  - ### Uses of NumberIsTooSmallException in org.apache.commons.math3.stat.inference

    Methods in org.apache.commons.math3.stat.inference that throw NumberIsTooSmallException
    Modifier and Type | Method and Description
    --- | ---
    `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 `StatisticalSummary` instances, 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 `sample1` and `sample2` are drawn from populations with the same mean, with significance level `alpha`, 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.`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 `sample1` and `sample2` is 0 in favor of the two-sided alternative that the mean paired difference is not equal to 0, with significance level `alpha`.
    `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)` Computes a t statistic to use in comparing the mean of the dataset described by `sampleStats` to `mu`.
    `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 `StatisticalSummary` instances, 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 `sample1` and `sample2` are drawn from populations with the same mean, with significance level `alpha`.
    `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 `sample` is drawn equals `mu`.
    `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 `sampleStats` with the constant `mu`.
    `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 `stats` is drawn equals `mu`.
    `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 `sampleStats1` and `sampleStats2` describe datasets drawn from populations with the same mean, with significance level `alpha`.

  - ### Uses of NumberIsTooSmallException in org.apache.commons.math3.util

    Methods in org.apache.commons.math3.util that throw NumberIsTooSmallException
    Modifier and Type | Method and Description
    --- | ---
    `protected void` | ResizableDoubleArray.`checkContractExpand(double contraction, double expansion)` Checks the expansion factor and the contraction criterion and raises an exception if the contraction criterion is smaller than the expansion criterion.

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