R: Test of Independece based on Marginal Ranks

ind.ctest {ICSNP} | R Documentation

## Test of Independece based on Marginal Ranks

### Description

Performs the test that a group of variables is independent of an other based on marginal ranks. Three different score functions are available.

### Usage

    ind.ctest(X, index1, index2 = NULL, scores = "rank",
              na.action = na.fail)

### Arguments

`X` | a data frame or matrix.
`index1` | integer vector that selects the columns of `X` that form group one. Only numeric columns can be selected.
`index2` | integer vector that selects the columns of `X` that form group two. Only numeric columns can be selected. If `NULL`, all remaining columns of X will be selected.
`scores` | if 'sign', a sign test is performed, if 'rank' a rank test is performed or if 'normal' a normal score test is performed.
`na.action` | a function which indicates what should happen when the data contain 'NA's. Default is to fail.

### Details

The test tests if X[ , index1] is independent of X[ , index2] and is described in great detail in Puri and Sen (1971).

### Value

A list with class 'htest' containing the following components:

`statistic` | the value of the W-statistic.
`parameter` | the degrees of freedom for the W-statistic.
`p.value` | the p-value for the test.
`method` | a character string indicating what type of test was performed.
`data.name` | a character string giving the name of the data.

### Author(s)

Klaus Nordhausen, klaus.nordhausen@uta.fi

### References

Puri , M.L. and Sen, P.K. (1971), Nonparametric Methods in Multivariate Analysis, New York: Wiley.

### Examples

    A1 <- matrix(c(4, 4, 5, 4, 6, 6, 5, 6, 7), ncol = 3)
    A2 <- matrix(c(0.5, -0.3, -0.3, 0.7), ncol = 2)
    X <- cbind(rmvnorm(100, c(-1, 0, 1), A1), rmvnorm(100, c(0, 0), A2))
    ind.ctest(X,1:3)
    ind.ctest(X, c(1, 5), c(2, 3), scores = "normal")

[Package ICSNP version 1.1-0 Index]