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

Packages that use NumberIsTooLargeException
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.solvers | Root finding algorithms, for univariate real functions.
org.apache.commons.math3.distribution | Implementations of common discrete and continuous distributions.
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.random | Random number and random data generators.
org.apache.commons.math3.special | Implementations of special functions such as Beta and Gamma.
org.apache.commons.math3.stat.inference | Classes providing hypothesis testing and confidence interval construction.
org.apache.commons.math3.util | Convenience routines and common data structures used throughout the commons-math library.

Uses of NumberIsTooLargeException in org.apache.commons.math3.analysis.differentiation

Methods in org.apache.commons.math3.analysis.differentiation that throw NumberIsTooLargeException
`double` | `DerivativeStructure.getPartialDerivative(int... orders)` Get a partial derivative.
`int` | `DSCompiler.getPartialDerivativeIndex(int... orders)` Get the index of a partial derivative in the array.

Constructors in org.apache.commons.math3.analysis.differentiation that throw NumberIsTooLargeException
`DerivativeStructure(int parameters, int order, int index, double value)` Build an instance representing a variable.
`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 NumberIsTooLargeException in org.apache.commons.math3.analysis.integration

Constructors in org.apache.commons.math3.analysis.integration that throw NumberIsTooLargeException
`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 NumberIsTooLargeException in org.apache.commons.math3.analysis.solvers

Methods in org.apache.commons.math3.analysis.solvers that throw NumberIsTooLargeException
`protected double` | `MullerSolver.doSolve()` Method for implementing actual optimization algorithms in derived classes.
`protected double` | `BracketingNthOrderBrentSolver.doSolve()` Method for implementing actual optimization algorithms in derived classes.
`protected double` | `BrentSolver.doSolve()` Method for implementing actual optimization algorithms in derived classes.
`protected double` | `MullerSolver2.doSolve()` Method for implementing actual optimization algorithms in derived classes.
`double` | `LaguerreSolver.doSolve()` Method for implementing actual optimization algorithms in derived classes.
`double` | `BracketingNthOrderBrentSolver.solve(int maxEval, UnivariateFunction f, double min, double max, AllowedSolution allowedSolution)` Solve for a zero in the given interval.
`double` | `BracketingNthOrderBrentSolver.solve(int maxEval, UnivariateFunction f, double min, double max, double startValue, AllowedSolution allowedSolution)` Solve for a zero in the given interval, start at `startValue`.
`protected void` | `BaseAbstractUnivariateSolver.verifyInterval(double lower, double upper)` Check that the endpoints specify an interval.
`static void` | `UnivariateSolverUtils.verifyInterval(double lower, double upper)` Check that the endpoints specify an interval.
`protected void` | `BaseAbstractUnivariateSolver.verifySequence(double lower, double initial, double upper)` Check that `lower < initial < upper`.
`static void` | `UnivariateSolverUtils.verifySequence(double lower, double initial, double upper)` Check that `lower < initial < upper`.

Uses of NumberIsTooLargeException in org.apache.commons.math3.distribution

Methods in org.apache.commons.math3.distribution that throw NumberIsTooLargeException
`double` | `LogNormalDistribution.cumulativeProbability(double x0, double x1)` Deprecated. See `RealDistribution.cumulativeProbability(double,double)`
`double` | `RealDistribution.cumulativeProbability(double x0, double x1)` Deprecated. As of 3.1. In 4.0, this method will be renamed `probability(double x0, double x1)`.
`double` | `AbstractRealDistribution.cumulativeProbability(double x0, double x1)` Deprecated. As of 3.1 (to be removed in 4.0). Please use `AbstractRealDistribution.probability(double,double)` instead.
`double` | `NormalDistribution.cumulativeProbability(double x0, double x1)` Deprecated. See `RealDistribution.cumulativeProbability(double,double)`
`double` | `AbstractIntegerDistribution.cumulativeProbability(int x0, int x1)` For a random variable `X` whose values are distributed according to this distribution, this method returns `P(x0 < X <= x1)`.
`double` | `IntegerDistribution.cumulativeProbability(int x0, int x1)` For a random variable `X` whose values are distributed according to this distribution, this method returns `P(x0 < X <= x1)`.
`double` | `LogNormalDistribution.probability(double x0, double x1)` For a random variable `X` whose values are distributed according to this distribution, this method returns `P(x0 < X <= x1)`.
`double` | `NormalDistribution.probability(double x0, double x1)` For a random variable `X` whose values are distributed according to this distribution, this method returns `P(x0 < X <= x1)`.

Constructors in org.apache.commons.math3.distribution that throw NumberIsTooLargeException
`HypergeometricDistribution(int populationSize, int numberOfSuccesses, int sampleSize)` Construct a new hypergeometric distribution with the specified population size, number of successes in the population, and sample size.
`HypergeometricDistribution(RandomGenerator rng, int populationSize, int numberOfSuccesses, int sampleSize)` Creates a new hypergeometric distribution.
`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.
`UniformIntegerDistribution(int lower, int upper)` Creates a new uniform integer distribution using the given lower and upper bounds (both inclusive).
`UniformIntegerDistribution(RandomGenerator rng, int lower, int upper)` Creates a new uniform integer distribution using the given lower and upper bounds (both inclusive).
`UniformRealDistribution(double lower, double upper)` Create a uniform real distribution using the given lower and upper bounds.
`UniformRealDistribution(double lower, double upper, double inverseCumAccuracy)` Create a uniform distribution.
`UniformRealDistribution(RandomGenerator rng, double lower, double upper, double inverseCumAccuracy)` Creates a uniform distribution.

Uses of NumberIsTooLargeException in org.apache.commons.math3.genetics

Methods in org.apache.commons.math3.genetics that throw NumberIsTooLargeException
`void` | `ListPopulation.addChromosome(Chromosome chromosome)` Add the given chromosome to the population.
`void` | `Population.addChromosome(Chromosome chromosome)` Add the given chromosome to the population.
`void` | `ListPopulation.addChromosomes(Collection<Chromosome> chromosomeColl)` Add a `Collection` of chromosomes to this `Population`.
`void` | `ListPopulation.setChromosomes(List<Chromosome> chromosomes)` Deprecated. use `ListPopulation.addChromosomes(Collection)` instead

Constructors in org.apache.commons.math3.genetics that throw NumberIsTooLargeException
`ElitisticListPopulation(List<Chromosome> chromosomes, int populationLimit, double elitismRate)` Creates a new `ElitisticListPopulation` instance.
`ListPopulation(List<Chromosome> chromosomes, int populationLimit)` Creates a new ListPopulation instance.

Uses of NumberIsTooLargeException in org.apache.commons.math3.linear

Methods in org.apache.commons.math3.linear that throw NumberIsTooLargeException
`OpenMapRealMatrix` | `OpenMapRealMatrix.createMatrix(int rowDimension, int columnDimension)` Deprecated. Create a new RealMatrix of the same type as the instance with the supplied row and column dimensions.
`OpenMapRealMatrix` | `OpenMapRealMatrix.multiply(OpenMapRealMatrix m)` Deprecated. Postmultiply this matrix by `m`.
`RealMatrix` | `OpenMapRealMatrix.multiply(RealMatrix m)` Deprecated. Returns the result of postmultiplying `this` by `m`.

Constructors in org.apache.commons.math3.linear that throw NumberIsTooLargeException
`ArrayFieldVector(Field<T> field, T[] d, int pos, int size)` Construct a vector from part of a array.
`ArrayFieldVector(T[] 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 a array.
`ArrayRealVector(Double[] d, int pos, int size)` Construct a vector from part of an array.
`OpenMapRealMatrix(int rowDimension, int columnDimension)` Deprecated. Build a sparse matrix with the supplied row and column dimensions.

Uses of NumberIsTooLargeException in org.apache.commons.math3.random

Methods in org.apache.commons.math3.random that throw NumberIsTooLargeException
`int` | `RandomDataGenerator.nextHypergeometric(int populationSize, int numberOfSuccesses, int sampleSize)` Generates a random value from the `Hypergeometric Distribution`.
`int` | `RandomDataImpl.nextHypergeometric(int populationSize, int numberOfSuccesses, int sampleSize)` Deprecated. Generates a random value from the `Hypergeometric Distribution`.
`int` | `RandomDataGenerator.nextInt(int lower, int upper)` Generates a uniformly distributed random integer between `lower` and `upper` (endpoints included).
`int` | `RandomData.nextInt(int lower, int upper)` Deprecated. Generates a uniformly distributed random integer between `lower` and `upper` (endpoints included).
`int` | `RandomDataImpl.nextInt(int lower, int upper)` Deprecated. Generates a uniformly distributed random integer between `lower` and `upper` (endpoints included).
`long` | `RandomDataGenerator.nextLong(long lower, long upper)` Generates a uniformly distributed random long integer between `lower` and `upper` (endpoints included).
`long` | `RandomData.nextLong(long lower, long upper)` Deprecated. Generates a uniformly distributed random long integer between `lower` and `upper` (endpoints included).
`long` | `RandomDataImpl.nextLong(long lower, long upper)` Deprecated. Generates a uniformly distributed random long integer between `lower` and `upper` (endpoints included).
`int[]` | `RandomDataGenerator.nextPermutation(int n, int k)` Generates an integer array of length `k` whose entries are selected randomly, without repetition, from the integers `0, ..., n - 1` (inclusive).
`int[]` | `RandomData.nextPermutation(int n, int k)` Deprecated. Generates an integer array of length `k` whose entries are selected randomly, without repetition, from the integers `0, ..., n - 1` (inclusive).
`int[]` | `RandomDataImpl.nextPermutation(int n, int k)` Deprecated. Generates an integer array of length `k` whose entries are selected randomly, without repetition, from the integers `0, ..., n - 1` (inclusive).
`Object[]` | `RandomDataGenerator.nextSample(Collection<?> c, int k)` Returns an array of `k` objects selected randomly from the Collection `c`.
`Object[]` | `RandomData.nextSample(Collection<?> c, int k)` Deprecated. Returns an array of `k` objects selected randomly from the Collection `c`.
`Object[]` | `RandomDataImpl.nextSample(Collection<?> c, int k)` Deprecated. Returns an array of `k` objects selected randomly from the Collection `c`.
`int` | `RandomDataGenerator.nextSecureInt(int lower, int upper)` Generates a uniformly distributed random integer between `lower` and `upper` (endpoints included) from a secure random sequence.
`int` | `RandomData.nextSecureInt(int lower, int upper)` Deprecated. Generates a uniformly distributed random integer between `lower` and `upper` (endpoints included) from a secure random sequence.
`int` | `RandomDataImpl.nextSecureInt(int lower, int upper)` Deprecated. Generates a uniformly distributed random integer between `lower` and `upper` (endpoints included) from a secure random sequence.
`long` | `RandomDataGenerator.nextSecureLong(long lower, long upper)` Generates a uniformly distributed random long integer between `lower` and `upper` (endpoints included) from a secure random sequence.
`long` | `RandomData.nextSecureLong(long lower, long upper)` Deprecated. Generates a uniformly distributed random long integer between `lower` and `upper` (endpoints included) from a secure random sequence.
`long` | `RandomDataImpl.nextSecureLong(long lower, long upper)` Deprecated. Generates a uniformly distributed random long integer between `lower` and `upper` (endpoints included) from a secure random sequence.
`double` | `RandomDataGenerator.nextUniform(double lower, double upper)` Generates a uniformly distributed random value from the open interval `(lower, upper)` (i.e., endpoints excluded).
`double` | `RandomData.nextUniform(double lower, double upper)` Deprecated. Generates a uniformly distributed random value from the open interval `(lower, upper)` (i.e., endpoints excluded).
`double` | `RandomDataImpl.nextUniform(double lower, double upper)` Deprecated. Generates a uniformly distributed random value from the open interval `(lower, upper)` (i.e., endpoints excluded).
`double` | `RandomDataGenerator.nextUniform(double lower, double upper, boolean lowerInclusive)` Generates a uniformly distributed random value from the interval `(lower, upper)` or the interval `[lower, upper)`.
`double` | `RandomData.nextUniform(double lower, double upper, boolean lowerInclusive)` Deprecated. Generates a uniformly distributed random value from the interval `(lower, upper)` or the interval `[lower, upper)`.
`double` | `RandomDataImpl.nextUniform(double lower, double upper, boolean lowerInclusive)` Deprecated. Generates a uniformly distributed random value from the interval `(lower, upper)` or the interval `[lower, upper)`.

Uses of NumberIsTooLargeException in org.apache.commons.math3.special

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

Uses of NumberIsTooLargeException in org.apache.commons.math3.stat.inference

Methods in org.apache.commons.math3.stat.inference that throw NumberIsTooLargeException
`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.

Uses of NumberIsTooLargeException in org.apache.commons.math3.util

Methods in org.apache.commons.math3.util that throw NumberIsTooLargeException
`static long` | `ArithmeticUtils.binomialCoefficient(int n, int k)` Returns an exact representation of the Binomial Coefficient, "`n choose k`", the number of `k`-element subsets that can be selected from an `n`-element set.
`static double` | `ArithmeticUtils.binomialCoefficientDouble(int n, int k)` Returns a `double` representation of the Binomial Coefficient, "`n choose k`", the number of `k`-element subsets that can be selected from an `n`-element set.
`static double` | `ArithmeticUtils.binomialCoefficientLog(int n, int k)` Returns the natural `log` of the Binomial Coefficient, "`n choose k`", the number of `k`-element subsets that can be selected from an `n`-element set.
`static long` | `ArithmeticUtils.stirlingS2(int n, int k)` Returns the Stirling number of the second kind, "`S(n,k)`", the number of ways of partitioning an `n`-element set into `k` non-empty subsets.

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