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java.lang.Object org.apache.commons.math3.stat.inference.WilcoxonSignedRankTest
public class WilcoxonSignedRankTest
An implementation of the Wilcoxon signedrank test.
Constructor Summary  

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

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

double 
wilcoxonSignedRank(double[] x,
double[] y)
Computes the Wilcoxon signed ranked statistic comparing mean for two related samples or repeated measurements on a single sample. 
double 
wilcoxonSignedRankTest(double[] x,
double[] y,
boolean exactPValue)
Returns the observed significance level, or pvalue, associated with a Wilcoxon signed ranked statistic comparing mean for two related samples or repeated measurements on a single sample. 
Methods inherited from class java.lang.Object 

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

public WilcoxonSignedRankTest()
public WilcoxonSignedRankTest(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 wilcoxonSignedRank(double[] x, double[] y) throws NullArgumentException, NoDataException, DimensionMismatchException
This statistic can be used to perform a Wilcoxon signed ranked test evaluating the null hypothesis that the two related samples or repeated measurements on a single sample has equal mean.
Let X_{i} denote the i'th individual of the first sample and Y_{i} the related i'th individual in the second sample. Let Z_{i} = Y_{i}  X_{i}.
Preconditions:
x
 the first sampley
 the second sample
NullArgumentException
 if x
or y
are null
.
NoDataException
 if x
or y
are zerolength.
DimensionMismatchException
 if x
and y
do not
have the same length.public double wilcoxonSignedRankTest(double[] x, double[] y, boolean exactPValue) throws NullArgumentException, NoDataException, DimensionMismatchException, NumberIsTooLargeException, ConvergenceException, MaxCountExceededException
Let X_{i} denote the i'th individual of the first sample and Y_{i} the related i'th individual in the second sample. Let Z_{i} = Y_{i}  X_{i}.
Preconditions:
x
 the first sampley
 the second sampleexactPValue
 if the exact pvalue is wanted (only works for x.length <= 30,
if true and x.length > 30, this is ignored because
calculations may take too long)
NullArgumentException
 if x
or y
are null
.
NoDataException
 if x
or y
are zerolength.
DimensionMismatchException
 if x
and y
do not
have the same length.
NumberIsTooLargeException
 if exactPValue
is true
and x.length
> 30
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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