Uses of Class
org.apache.commons.math3.exception.ZeroException

Packages that use ZeroException
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.linear Linear algebra support. 
org.apache.commons.math3.random Random number and random data generators. 
org.apache.commons.math3.stat.inference Classes providing hypothesis testing and confidence interval construction. 
 

Uses of ZeroException in org.apache.commons.math3.analysis.interpolation
 

Methods in org.apache.commons.math3.analysis.interpolation that throw ZeroException
 void HermiteInterpolator.addSamplePoint(double x, double[]... value)
          Add a sample point.
 

Uses of ZeroException in org.apache.commons.math3.complex
 

Methods in org.apache.commons.math3.complex that throw ZeroException
 void RootsOfUnity.computeRoots(int n)
           Computes the n-th roots of unity.
 

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

Methods in org.apache.commons.math3.linear that throw ZeroException
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.math3.linear that throw ZeroException
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.math3.random
 

Methods in org.apache.commons.math3.random that throw ZeroException
 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 valuesFileURL and binCount bins.
 void EmpiricalDistribution.load(URL url)
          Computes the empirical distribution using data read from a URL.
 

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

Methods in org.apache.commons.math3.stat.inference that throw ZeroException
static double TestUtils.chiSquareDataSetsComparison(long[] observed1, long[] observed2)
           
 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.chiSquareTestDataSetsComparison(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.
static boolean TestUtils.chiSquareTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)
           
 boolean ChiSquareTest.chiSquareTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)
          Performs a Chi-Square two sample test comparing two binned data sets.
static double TestUtils.gDataSetsComparison(long[] observed1, long[] observed2)
           
 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.gTestDataSetsComparison(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.
static boolean TestUtils.gTestDataSetsComparison(long[] observed1, long[] observed2, double alpha)
           
 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.rootLogLikelihoodRatio(long k11, long k12, long k21, long k22)
           
 



Copyright © 2003-2012 The Apache Software Foundation. All Rights Reserved.