R: Test for no correlation between paired sampes

cor.test_eq {MatrixCorrelation} | R Documentation

## Test for no correlation between paired sampes

### Description

Permutation test for squared Pearson correlation between to vectors of samples.

### Usage

    cor.test_eq(x, y, B = 10000)

### Arguments

`x` | first `vector` to be compared (or two column `matrix/data.frame`).
`y` | second `vector` to be compared (ommit if included in `x`).
`B` | integer number of permutations, default = 10000.

### Details

This is a convenience function combining `SMI` and `significant` for the special case of vector vs vector comparisons. The nullhypothesis is that the correlation between the vectors is +/-1, while significance signifies a deviance toward 0.

### Value

A value indicating if the two input vectors are signficantly different.

### Author(s)

Kristian Hovde Liland

### References

Similarity of Matrices Index - Ulf Geir Indahl, Tormod Næs, Kristian Hovde Liland

### See Also

`plot.SMI` (print.SMI/summary.SMI), `RV` (RV2/RVadj), `r1` (r2/r3/r4/GCD), `allCorrelations` (matrix correlation comparison), `PCAcv (cross-validated PCA)`.

### Examples

    a <- (1:5) + rnorm(5)
    b <- (1:5) + rnorm(5)
    cor.test_eq(a,b)

[Package MatrixCorrelation version 0.9.5 Index]