cov.test: Significance test for the covariance between two datasets
In RVAideMemoire: Testing and Plotting Procedures for Biostatistics

cov.test

R Documentation

Significance test for the covariance between two datasets

Description

Performs a permutation test based on the sum of square covariance between variables of two datasets, to test wether the (square) covariance is higher than expected under random association between the two datasets. The test is relevent parallel to a 2B-PLS.

Usage

cov.test(X, Y, scale.X = TRUE, scale.Y = TRUE, nperm = 999, progress = TRUE)

Arguments

`X`	a numeric vector, matrix or data frame.
`Y`	a numeric vector, matrix or data frame.
`scale.X`	logical, if `TRUE` (default) scaling of `X` is required.
`scale.Y`	logical, if `TRUE` (default) scaling of `Y` is required.
`nperm`	number of permutations.
`progress`	logical indicating if the progress bar should be displayed.

Details

The function deals with the limitted floating point precision, which can bias calculation of p-values based on a discrete test statistic distribution.

Value

`method`	a character string indicating the name of the test.
`data.name`	a character string giving the name(s) of the data, plus additional information.
`statistic`	the value of the test statistics.
`permutations`	the number of permutations.
`p.value`	the p-value of the test.