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java.lang.Object org.apache.commons.math3.stat.inference.MannWhitneyUTest
public class MannWhitneyUTest
An implementation of the MannWhitney U test (also called Wilcoxon ranksum test).
Constructor Summary  

MannWhitneyUTest()
Create a test instance using where NaN's are left in place and ties get the average of applicable ranks. 

MannWhitneyUTest(NaNStrategy nanStrategy,
TiesStrategy tiesStrategy)
Create a test instance using the given strategies for NaN's and ties. 
Method Summary  

double 
mannWhitneyU(double[] x,
double[] y)
Computes the MannWhitney U statistic comparing mean for two independent samples possibly of different length. 
double 
mannWhitneyUTest(double[] x,
double[] y)
Returns the asymptotic observed significance level, or pvalue, associated with a MannWhitney U statistic comparing mean for two independent samples. 
Methods inherited from class java.lang.Object 

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait 
Constructor Detail 

public MannWhitneyUTest()
public MannWhitneyUTest(NaNStrategy nanStrategy, TiesStrategy tiesStrategy)
nanStrategy
 specifies the strategy that should be used for Double.NaN'stiesStrategy
 specifies the strategy that should be used for tiesMethod Detail 

public double mannWhitneyU(double[] x, double[] y) throws NullArgumentException, NoDataException
This statistic can be used to perform a MannWhitney U test evaluating the null hypothesis that the two independent samples has equal mean.
Let X_{i} denote the i'th individual of the first sample and Y_{j} the j'th individual in the second sample. Note that the samples would often have different length.
Preconditions:
x
 the first sampley
 the second sample
NullArgumentException
 if x
or y
are null
.
NoDataException
 if x
or y
are zerolength.public double mannWhitneyUTest(double[] x, double[] y) throws NullArgumentException, NoDataException, ConvergenceException, MaxCountExceededException
Let X_{i} denote the i'th individual of the first sample and Y_{j} the j'th individual in the second sample. Note that the samples would often have different length.
Preconditions:
Ties give rise to biased variance at the moment. See e.g. http://mlsc.lboro.ac.uk/resources/statistics/Mannwhitney.pdf.
x
 the first sampley
 the second sample
NullArgumentException
 if x
or y
are null
.
NoDataException
 if x
or y
are zerolength.
ConvergenceException
 if the pvalue can not be computed due to a
convergence error
MaxCountExceededException
 if the maximum number of iterations
is exceeded


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