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

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
...: further arguments passed to or from other methods

Value

returns a list of class 'rtest'

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.

Author

Daniel Chessel

Examples

data(doubs)
pca1 <- dudi.pca(doubs$env, scal = TRUE, scann = FALSE)
pca2 <- dudi.pca(doubs$fish, scal = FALSE, scann = FALSE)
rv1 <- RV.rtest(pca1$tab, pca2$tab, 99)
rv1
#> Monte-Carlo test
#> Call: RV.rtest(df1 = pca1$tab, df2 = pca2$tab, nrepet = 99)
#> 
#> Observation: 0.4505569 
#> 
#> Based on 99 replicates
#> Simulated p-value: 0.01 
#> Alternative hypothesis: greater 
#> 
#>     Std.Obs Expectation    Variance 
#>  7.23431835  0.08981169  0.00248660 
plot(rv1)