## Monte-Carlo Test on the sum of the singular values of a procustean rotation (in C).

### Description

performs a Monte-Carlo Test on the sum of the singular values of a procustean rotation.

### Usage

```procuste.randtest(df1, df2, nrepet = 999)
```

### Arguments

 `df1` a data frame `df2` a data frame `nrepet` the number of permutations

### Value

returns a list of class `randtest`

### References

Jackson, D.A. (1995) PROTEST: a PROcustean randomization TEST of community environment concordance. Ecosciences, 2, 297–303.

### Examples

```data(doubs)
pca1 <- dudi.pca(doubs\$mil, scal = TRUE, scann = FALSE)
pca2 <- dudi.pca(doubs\$poi, scal = FALSE, scann = FALSE)
protest1 <- procuste.randtest(pca1\$tab, pca2\$tab, 999)
protest1
plot(protest1,main="PROTEST")
```

### Worked out examples

```
> ### Name: procuste.randtest
> ### Title: Monte-Carlo Test on the sum of the singular values of a
> ###   procustean rotation (in C).
> ### Aliases: procuste.randtest
> ### Keywords: multivariate nonparametric
>
> ### ** Examples
>
> data(doubs)
> pca1 <- dudi.pca(doubs\$mil, scal = TRUE, scann = FALSE)
> pca2 <- dudi.pca(doubs\$poi, scal = FALSE, scann = FALSE)
> protest1 <- procuste.randtest(pca1\$tab, pca2\$tab, 999)
> protest1
Monte-Carlo test
Call: procuste.randtest(df1 = pca1\$tab, df2 = pca2\$tab, nrepet = 999)

Observation: 0.6562

Based on 999 replicates
Simulated p-value: 0.001
Alternative hypothesis: greater

Std.Obs Expectation    Variance
6.584401804 0.342097252 0.002275678
> plot(protest1,main="PROTEST")
```
```>
>
>
>
```