Uses of Class
org.apache.commons.math4.exception.ZeroException

Packages that use ZeroException

Package	Description
org.apache.commons.math4.analysis.interpolation	Univariate real functions interpolation algorithms.
org.apache.commons.math4.distribution	Implementations of common discrete and continuous distributions.
org.apache.commons.math4.linear	Linear algebra support.
org.apache.commons.math4.stat.inference	Classes providing hypothesis testing.

Uses of ZeroException in org.apache.commons.math4.analysis.interpolation

Methods in org.apache.commons.math4.analysis.interpolation that throw ZeroException

Modifier and Type	Method	Description
void	FieldHermiteInterpolator.addSamplePoint(T x, T[]... value)	Add a sample point.
void	HermiteInterpolator.addSamplePoint(double x, double[]... value)	Add a sample point.

Uses of ZeroException in org.apache.commons.math4.distribution

Methods in org.apache.commons.math4.distribution that throw ZeroException

Modifier and Type	Method	Description
void	EmpiricalDistribution.load(java.net.URL url)	Computes the empirical distribution using data read from a URL.

Uses of ZeroException in org.apache.commons.math4.linear

Methods in org.apache.commons.math4.linear that throw ZeroException

Modifier and Type	Method	Description
static <T extends FieldElement<T>> FieldVector<T>	MatrixUtils.createFieldVector(T[] data)	Creates a FieldVector using the data from the input array.

Constructors in org.apache.commons.math4.linear that throw ZeroException

Constructor	Description
ArrayFieldVector(Field<T> field, 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[] d, boolean copyArray)	Create a new ArrayFieldVector using the input array as the underlying data array.
ArrayFieldVector(T[] v1, T[] v2)	Construct a vector by appending one vector to another vector.

Uses of ZeroException in org.apache.commons.math4.stat.inference

Methods in org.apache.commons.math4.stat.inference that throw ZeroException

Modifier and Type	Method	Description
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	InferenceTestUtils.chiSquareDataSetsComparison(long[] observed1, long[] observed2)
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	InferenceTestUtils.chiSquareTestDataSetsComparison(long[] observed1, long[] observed2)
static boolean	InferenceTestUtils.chiSquareTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)
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	InferenceTestUtils.gDataSetsComparison(long[] observed1, long[] observed2)
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	InferenceTestUtils.gTestDataSetsComparison(long[] observed1, long[] observed2)
static boolean	InferenceTestUtils.gTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)
static double	InferenceTestUtils.rootLogLikelihoodRatio(long k11, long k12, long k21, long k22)