# permutest: Permutation Test P-value for Multivaraite Correlation In CORREP: Multivariate Correlation Estimator and Statistical Inference Procedures.

## Description

This function calculates p-values of the multivariate correlation estimator by enumerating all permutations. We recommend using Likehood Ratio Test implemented in function cor.LRtest if your data has moderate to large sample size (>5) The procedure is same as those permutation tests for Pearson correlation coefficient or other parameters. Since the approximation of null distribution requires enumerating all permutations. The computational burden increases in \$n^2\$.

## Usage

 `1` ```permutest(x, y=NULL, m, G) ```

## Arguments

 `x` data matrix, column represents samples (conditions), and row represents variables (genes), see example below for format information `y` optional, used when x and y are vectors `m` number of replicates `G` number of genes

See manuscript.

## Value

 `PV` P-values of permutation tests

## Author(s)

Dongxiao Zhu and Youjuan Li

## References

Zhu, D and Li Y. 2007. Multivariate Correlation Estimator for Inferring Functional Relationships from Replicated 'OMICS' data. Submitted.

`cor.LRtest`, `cor.LRtest.std`, `cor.test`

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10``` ```library("CORREP") library("e1071") d0 <- NULL ## sample size is set to 5, it takes about a min to finish for(l in 1:5) d0 <- rbind(d0, rnorm(100)) ## data must have row variance of 1 d0.std <- apply(d0, 2, function(x) x/sd(x)) M <- cor.balance(t(d0.std), m = 4, G= 25) M.pv <- permutest(t(d0.std), m = 4, G= 25) ```

### Example output

```
```

CORREP documentation built on Nov. 8, 2020, 5:09 p.m.