## Monte-Carlo Test on the sum of eigenvalues of a co-inertia analysis (in R).

### Description

performs a Monte-Carlo Test on the sum of eigenvalues of a co-inertia analysis.

### Usage

```RV.rtest(df1, df2, nrepet = 99)
```

### Arguments

 `df1, df2` two data frames with the same rows `nrepet` the number of permutations

### Value

returns a list of class 'rtest'

Daniel Chessel

### References

Heo, M. & Gabriel, K.R. (1997) A permutation test of association between configurations by means of the RV coefficient. Communications in Statistics - Simulation and Computation, 27, 843-856.

### Examples

```data(doubs)
pca1 <- dudi.pca(doubs\$mil, scal = TRUE, scann = FALSE)
pca2 <- dudi.pca(doubs\$poi, scal = FALSE, scann = FALSE)
rv1 <- RV.rtest(pca1\$tab, pca2\$tab, 99)
rv1
plot(rv1)
```

### Worked out examples

```
> ### Name: RV.rtest
> ### Title: Monte-Carlo Test on the sum of eigenvalues of a co-inertia
> ###   analysis (in R).
> ### Aliases: RV.rtest
> ### Keywords: multivariate nonparametric
>
> ### ** Examples
>
> data(doubs)
> pca1 <- dudi.pca(doubs\$mil, scal = TRUE, scann = FALSE)
> pca2 <- dudi.pca(doubs\$poi, scal = FALSE, scann = FALSE)
> rv1 <- RV.rtest(pca1\$tab, pca2\$tab, 99)
> rv1
Monte-Carlo test
Observation: 0.4505569
Call: RV.rtest(df1 = pca1\$tab, df2 = pca2\$tab, nrepet = 99)
Based on 99 replicates
Simulated p-value: 0.01
> plot(rv1)
```
```>
>
>
>
```