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

Value

returns a list of class 'rtest'

Author(s)

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

> library(ade4)
> ### 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)

> 
> 
> 
>