WilcoxonSignedRankTest (Apache Commons Math 3.6.1 API)

java.lang.Object
- org.apache.commons.math3.stat.inference.WilcoxonSignedRankTest

public class WilcoxonSignedRankTest
extends Object

An implementation of the Wilcoxon signed-rank test.

Constructor Summary

Constructors
Constructor and Description
`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

Methods
Modifier and Type	Method and Description
`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 p-value, 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
  - WilcoxonSignedRankTest
```
public WilcoxonSignedRankTest()
```
    Create a test instance where NaN's are left in place and ties get the average of applicable ranks. Use this unless you are very sure of what you are doing.
  - WilcoxonSignedRankTest
```
public WilcoxonSignedRankTest(NaNStrategy nanStrategy,
                      TiesStrategy tiesStrategy)
```
    Create a test instance using the given strategies for NaN's and ties. Only use this if you are sure of what you are doing.
    
    Parameters:
    nanStrategy - specifies the strategy that should be used for Double.NaN's
    tiesStrategy - specifies the strategy that should be used for ties
- Method Detail
  - wilcoxonSignedRank
```
public double wilcoxonSignedRank(double[] x,
                        double[] y)
                          throws NullArgumentException,
                                 NoDataException,
                                 DimensionMismatchException
```
    Computes the Wilcoxon signed ranked statistic comparing mean for two related samples or repeated measurements on a single sample.
    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:
    - The differences Z_i must be independent.
    - Each Z_i comes from a continuous population (they must be identical) and is symmetric about a common median.
    - The values that X_i and Y_i represent are ordered, so the comparisons greater than, less than, and equal to are meaningful.
    Parameters:
    x - the first sample
    y - the second sample
    
    Returns:
    wilcoxonSignedRank statistic (the larger of W+ and W-)
    
    Throws:
    
    NullArgumentException - if x or y are null.
    
    NoDataException - if x or y are zero-length.
    
    DimensionMismatchException - if x and y do not have the same length.
  - wilcoxonSignedRankTest
```
public double wilcoxonSignedRankTest(double[] x,
                            double[] y,
                            boolean exactPValue)
                              throws NullArgumentException,
                                     NoDataException,
                                     DimensionMismatchException,
                                     NumberIsTooLargeException,
                                     ConvergenceException,
                                     MaxCountExceededException
```
    Returns the observed significance level, or p-value, associated with a Wilcoxon signed ranked statistic comparing mean for two related samples or repeated measurements on a single sample.
    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:
    - The differences Z_i must be independent.
    - Each Z_i comes from a continuous population (they must be identical) and is symmetric about a common median.
    - The values that X_i and Y_i represent are ordered, so the comparisons greater than, less than, and equal to are meaningful.
    Parameters:
    x - the first sample
    y - the second sample
    exactPValue - if the exact p-value is wanted (only works for x.length <= 30, if true and x.length > 30, this is ignored because calculations may take too long)
    
    Returns:
    p-value
    
    Throws:
    
    NullArgumentException - if x or y are null.
    
    NoDataException - if x or y are zero-length.
    
    DimensionMismatchException - if x and y do not have the same length.
    
    NumberIsTooLargeException - if exactPValue is true and x.length > 30
    
    ConvergenceException - if the p-value can not be computed due to a convergence error
    
    MaxCountExceededException - if the maximum number of iterations is exceeded

Class WilcoxonSignedRankTest

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

WilcoxonSignedRankTest

WilcoxonSignedRankTest

Method Detail

wilcoxonSignedRank

wilcoxonSignedRankTest