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MXM (version 0.9.7)

Permutation based p-value for the Pearson correlation coefficient: Permutation based p-value for the Pearson correlation coefficient

Description

The main task of this test is to provide a p-value PVALUE for the null hypothesis: feature 'X' is independent from 'TARGET' given a conditioning set CS.

Usage

permcor(x, R = 999)

Arguments

x
A matrix with two columns, two continuous variables.
R
The number of permutations to be conducted; set to 999 by default.

Value

A vector consisting of two values, the Pearson correlation and the permutation based p-value.

Details

This is a computational non parametric correlation coefficient test and is advised to be used when a small sample size is available.

References

Legendre Pierre (2000). Comparison of permutation methods for the partial correlation and partial Mantel tests. Journal of Statistical Computation and Simulation 67(1):37-73.

See Also

pc.skel, testIndSpearman, testIndFisher, SES, CondIndTests

Examples

Run this code
permcor(iris[,1:2])
permcor(iris[,1:2], R = 9999)

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