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

Packages that use NotPositiveException
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.interpolation
Univariate real functions interpolation algorithms.
org.apache.commons.math3.complex
Complex number type and implementations of complex transcendental 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.ml.clustering
Clustering algorithms.
org.apache.commons.math3.optim.nonlinear.scalar.noderiv
This package provides optimization algorithms that do not require derivatives.
org.apache.commons.math3.optimization.direct
This package provides optimization algorithms that don't require derivatives.
org.apache.commons.math3.random
Random number and random data generators.
org.apache.commons.math3.stat.clustering
All classes and sub-packages of this package are deprecated.
org.apache.commons.math3.stat.inference
Classes providing hypothesis testing.
org.apache.commons.math3.stat.interval
Classes providing binomial proportion confidence interval construction.
org.apache.commons.math3.util
Convenience routines and common data structures used throughout the commons-math library.

## Uses of NotPositiveException in org.apache.commons.math3.analysis.differentiation

Constructors in org.apache.commons.math3.analysis.differentiation that throw NotPositiveException
Modifier
Constructor
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 NotPositiveException in org.apache.commons.math3.analysis.interpolation

Constructors in org.apache.commons.math3.analysis.interpolation that throw NotPositiveException
Modifier
Constructor
Description
``
`LoessInterpolator(double bandwidth, int robustnessIters, double accuracy)`
Construct a new `LoessInterpolator` with given bandwidth, number of robustness iterations and accuracy.
``
`MicrosphereInterpolator(int elements, int exponent)`
Deprecated.
Create a microsphere interpolator.
``
`MicrosphereProjectionInterpolator(InterpolatingMicrosphere microsphere, double exponent, boolean sharedSphere, double noInterpolationTolerance)`
Create a microsphere interpolator.
``
`SmoothingPolynomialBicubicSplineInterpolator(int degree)`
Deprecated.
``
`SmoothingPolynomialBicubicSplineInterpolator(int xDegree, int yDegree)`
Deprecated.

## Uses of NotPositiveException in org.apache.commons.math3.complex

Methods in org.apache.commons.math3.complex that throw NotPositiveException
Modifier and Type
Method
Description
`List<Complex>`
Complex.`nthRoot(int n)`
Computes the n-th roots of this complex number.

## Uses of NotPositiveException in org.apache.commons.math3.distribution

Constructors in org.apache.commons.math3.distribution that throw NotPositiveException
Modifier
Constructor
Description
``
`EnumeratedDistribution(List<Pair<T,Double>> pmf)`
Create an enumerated distribution using the given probability mass function enumeration.
``
`EnumeratedDistribution(RandomGenerator rng, List<Pair<T,Double>> pmf)`
Create an enumerated distribution using the given random number generator and probability mass function enumeration.
``
`EnumeratedIntegerDistribution(int[] singletons, double[] probabilities)`
Create a discrete distribution using the given probability mass function definition.
``
`EnumeratedIntegerDistribution(RandomGenerator rng, int[] singletons, double[] probabilities)`
Create a discrete distribution using the given random number generator and probability mass function definition.
``
`EnumeratedRealDistribution(double[] singletons, double[] probabilities)`
Create a discrete real-valued distribution using the given probability mass function enumeration.
``
`EnumeratedRealDistribution(RandomGenerator rng, double[] singletons, double[] probabilities)`
Create a discrete real-valued distribution using the given random number generator and probability mass function enumeration.
``
`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.
``
`MixtureMultivariateNormalDistribution(RandomGenerator rng, List<Pair<Double,MultivariateNormalDistribution>> components)`
Creates a mixture model from a list of distributions and their associated weights.

## Uses of NotPositiveException in org.apache.commons.math3.genetics

Methods in org.apache.commons.math3.genetics that throw NotPositiveException
Modifier and Type
Method
Description
`void`
ListPopulation.`setPopulationLimit(int populationLimit)`
Sets the maximal population size.
Constructors in org.apache.commons.math3.genetics that throw NotPositiveException
Modifier
Constructor
Description
``
`ElitisticListPopulation(int populationLimit, double elitismRate)`
Creates a new `ElitisticListPopulation` instance and initializes its inner chromosome list.
``
`ElitisticListPopulation(List<Chromosome> chromosomes, int populationLimit, double elitismRate)`
Creates a new `ElitisticListPopulation` instance.
``
`ListPopulation(int populationLimit)`
Creates a new ListPopulation instance and initializes its inner chromosome list.
``
`ListPopulation(List<Chromosome> chromosomes, int populationLimit)`
Creates a new ListPopulation instance.

## Uses of NotPositiveException in org.apache.commons.math3.linear

Methods in org.apache.commons.math3.linear that throw NotPositiveException
Modifier and Type
Method
Description
`FieldVector<T>`
ArrayFieldVector.`getSubVector(int index, int n)`
Get a subvector from consecutive elements.
`RealVector`
ArrayRealVector.`getSubVector(int index, int n)`
Get a subvector from consecutive elements.
`FieldVector<T>`
FieldVector.`getSubVector(int index, int n)`
Get a subvector from consecutive elements.
`OpenMapRealVector`
OpenMapRealVector.`getSubVector(int index, int n)`
Get a subvector from consecutive elements.
`abstract RealVector`
RealVector.`getSubVector(int index, int n)`
Get a subvector from consecutive elements.
`FieldVector<T>`
SparseFieldVector.`getSubVector(int index, int n)`
Get a subvector from consecutive elements.
`FieldMatrix<T>`
AbstractFieldMatrix.`power(int p)`
Returns the result multiplying this with itself `p` times.
`RealMatrix`
AbstractRealMatrix.`power(int p)`
Returns the result of multiplying `this` with itself `p` times.
`FieldMatrix<T>`
FieldMatrix.`power(int p)`
Returns the result multiplying this with itself `p` times.
`RealMatrix`
RealMatrix.`power(int p)`
Returns the result of multiplying `this` with itself `p` times.

## Uses of NotPositiveException in org.apache.commons.math3.ml.clustering

Constructors in org.apache.commons.math3.ml.clustering that throw NotPositiveException
Modifier
Constructor
Description
``
`DBSCANClusterer(double eps, int minPts)`
Creates a new instance of a DBSCANClusterer.
``
`DBSCANClusterer(double eps, int minPts, DistanceMeasure measure)`
Creates a new instance of a DBSCANClusterer.

## Uses of NotPositiveException in org.apache.commons.math3.optim.nonlinear.scalar.noderiv

Constructors in org.apache.commons.math3.optim.nonlinear.scalar.noderiv that throw NotPositiveException
Modifier
Constructor
Description
``
`Sigma(double[] s)`

## Uses of NotPositiveException in org.apache.commons.math3.optimization.direct

Constructors in org.apache.commons.math3.optimization.direct that throw NotPositiveException
Modifier
Constructor
Description
``
`Sigma(double[] s)`

## Uses of NotPositiveException in org.apache.commons.math3.random

Methods in org.apache.commons.math3.random that throw NotPositiveException
Modifier and Type
Method
Description
`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`.
`double[]`
HaltonSequenceGenerator.`skipTo(int index)`
Skip to the i-th point in the Halton sequence.
`double[]`
SobolSequenceGenerator.`skipTo(int index)`
Skip to the i-th point in the Sobol sequence.

## Uses of NotPositiveException in org.apache.commons.math3.stat.clustering

Constructors in org.apache.commons.math3.stat.clustering that throw NotPositiveException
Modifier
Constructor
Description
``
`DBSCANClusterer(double eps, int minPts)`
Deprecated.
Creates a new instance of a DBSCANClusterer.

## Uses of NotPositiveException in org.apache.commons.math3.stat.inference

Methods in org.apache.commons.math3.stat.inference that throw NotPositiveException
Modifier and Type
Method
Description
`double`
ChiSquareTest.`chiSquare(double[] expected, long[] observed)`
Computes the Chi-Square statistic comparing `observed` and `expected` frequency counts.
`double`
ChiSquareTest.`chiSquare(long[][] counts)`
Computes the Chi-Square statistic associated with a chi-square test of independence based on the input `counts` array, viewed as a two-way table.
`static double`
TestUtils.`chiSquare(double[] expected, long[] observed)`
`static double`
TestUtils.`chiSquare(long[][] counts)`
`double`
ChiSquareTest.`chiSquareDataSetsComparison(long[] observed1, long[] observed2)`
Computes a Chi-Square two sample test statistic comparing bin frequency counts in `observed1` and `observed2`.
`static double`
TestUtils.`chiSquareDataSetsComparison(long[] observed1, long[] observed2)`
`double`
ChiSquareTest.`chiSquareTest(double[] expected, long[] observed)`
Returns the observed significance level, or p-value, associated with a Chi-square goodness of fit test comparing the `observed` frequency counts to those in the `expected` array.
`boolean`
ChiSquareTest.`chiSquareTest(double[] expected, long[] observed, double alpha)`
Performs a Chi-square goodness of fit test evaluating the null hypothesis that the observed counts conform to the frequency distribution described by the expected counts, with significance level `alpha`.
`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 `counts` array, viewed as a two-way table.
`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.`chiSquareTest(double[] expected, long[] observed)`
`static boolean`
TestUtils.`chiSquareTest(double[] expected, long[] observed, double alpha)`
`static double`
TestUtils.`chiSquareTest(long[][] counts)`
`static boolean`
TestUtils.`chiSquareTest(long[][] counts, double alpha)`
`double`
ChiSquareTest.`chiSquareTestDataSetsComparison(long[] observed1, long[] observed2)`
Returns the observed significance level, or p-value, associated with a Chi-Square two sample test comparing bin frequency counts in `observed1` and `observed2`.
`boolean`
ChiSquareTest.`chiSquareTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)`
Performs a Chi-Square two sample test comparing two binned data sets.
`static double`
TestUtils.`chiSquareTestDataSetsComparison(long[] observed1, long[] observed2)`
`static boolean`
TestUtils.`chiSquareTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)`
`double`
GTest.`g(double[] expected, long[] observed)`
Computes the G statistic for Goodness of Fit comparing `observed` and `expected` frequency counts.
`static double`
TestUtils.`g(double[] expected, long[] observed)`
`double`
GTest.`gDataSetsComparison(long[] observed1, long[] observed2)`
Computes a G (Log-Likelihood Ratio) two sample test statistic for independence comparing frequency counts in `observed1` and `observed2`.
`static double`
TestUtils.`gDataSetsComparison(long[] observed1, long[] observed2)`
`double`
GTest.`gTest(double[] expected, long[] observed)`
Returns the observed significance level, or p-value, associated with a G-Test for goodness of fit comparing the `observed` frequency counts to those in the `expected` array.
`boolean`
GTest.`gTest(double[] expected, long[] observed, double alpha)`
Performs a G-Test (Log-Likelihood Ratio Test) for goodness of fit evaluating the null hypothesis that the observed counts conform to the frequency distribution described by the expected counts, with significance level `alpha`.
`static double`
TestUtils.`gTest(double[] expected, long[] observed)`
`static boolean`
TestUtils.`gTest(double[] expected, long[] observed, double alpha)`
`double`
GTest.`gTestDataSetsComparison(long[] observed1, long[] observed2)`
Returns the observed significance level, or p-value, associated with a G-Value (Log-Likelihood Ratio) for two sample test comparing bin frequency counts in `observed1` and `observed2`.
`boolean`
GTest.`gTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)`
Performs a G-Test (Log-Likelihood Ratio Test) comparing two binned data sets.
`static double`
TestUtils.`gTestDataSetsComparison(long[] observed1, long[] observed2)`
`static boolean`
TestUtils.`gTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)`
`double`
GTest.`gTestIntrinsic(double[] expected, long[] observed)`
Returns the intrinsic (Hardy-Weinberg proportions) p-Value, as described in p64-69 of McDonald, J.H.
`static double`
TestUtils.`gTestIntrinsic(double[] expected, long[] observed)`
`static double`
TestUtils.`rootLogLikelihoodRatio(long k11, long k12, long k21, long k22)`

## Uses of NotPositiveException in org.apache.commons.math3.stat.interval

Methods in org.apache.commons.math3.stat.interval that throw NotPositiveException
Modifier and Type
Method
Description
`ConfidenceInterval`
BinomialConfidenceInterval.`createInterval(int numberOfTrials, int numberOfSuccesses, double confidenceLevel)`
Create a confidence interval for the true probability of success of an unknown binomial distribution with the given observed number of trials, successes and confidence level.

## Uses of NotPositiveException in org.apache.commons.math3.util

Methods in org.apache.commons.math3.util that throw NotPositiveException
Modifier and Type
Method
Description
`static long`
ArithmeticUtils.`binomialCoefficient(int n, int k)`
Deprecated.
use `CombinatoricsUtils.binomialCoefficient(int, int)`
`static long`
CombinatoricsUtils.`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)`
Deprecated.
use `CombinatoricsUtils.binomialCoefficientDouble(int, int)`
`static double`
CombinatoricsUtils.`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)`
Deprecated.
use `CombinatoricsUtils.binomialCoefficientLog(int, int)`
`static double`
CombinatoricsUtils.`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 void`
CombinatoricsUtils.`checkBinomial(int n, int k)`
Check binomial preconditions.
`static void`
MathArrays.`checkNonNegative(long[] in)`
Check that all entries of the input array are >= 0.
`static void`
MathArrays.`checkNonNegative(long[][] in)`
Check all entries of the input array are >= 0.
`static long`
ArithmeticUtils.`factorial(int n)`
Deprecated.
use `CombinatoricsUtils.factorial(int)`
`static long`
CombinatoricsUtils.`factorial(int n)`
Returns n!.
`static double`
ArithmeticUtils.`factorialDouble(int n)`
Deprecated.
use `CombinatoricsUtils.factorialDouble(int)`
`static double`
CombinatoricsUtils.`factorialDouble(int n)`
Compute n!, the factorial of `n` (the product of the numbers 1 to n), as a `double`.
`static double`
ArithmeticUtils.`factorialLog(int n)`
Deprecated.
use `CombinatoricsUtils.factorialLog(int)`
`static double`
CombinatoricsUtils.`factorialLog(int n)`
Compute the natural logarithm of the factorial of `n`.
`static int`
ArithmeticUtils.`pow(int k, int e)`
Raise an int to an int power.
`static int`
ArithmeticUtils.`pow(int k, long e)`
Deprecated.
As of 3.3.
`static long`
ArithmeticUtils.`pow(long k, int e)`
Raise a long to an int power.
`static long`
ArithmeticUtils.`pow(long k, long e)`
Deprecated.
As of 3.3.
`static BigInteger`
ArithmeticUtils.`pow(BigInteger k, int e)`
Raise a BigInteger to an int power.
`static BigInteger`
ArithmeticUtils.`pow(BigInteger k, long e)`
Raise a BigInteger to a long power.
`static BigInteger`
ArithmeticUtils.`pow(BigInteger k, BigInteger e)`
Raise a BigInteger to a BigInteger power.
`static long`
ArithmeticUtils.`stirlingS2(int n, int k)`
Deprecated.
use `CombinatoricsUtils.stirlingS2(int, int)`
`static long`
CombinatoricsUtils.`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.