Monte-Carlo Test on the percentage of explained (i.e. constrained) inertia

Performs a Monte-Carlo test on on the percentage of explained (i.e. constrained) inertia. The statistic is the ratio of the inertia (sum of eigenvalues) of the constrained analysis divided by the inertia of the unconstrained analysis.

Usage

# S3 method for class 'pcaiv'
randtest(xtest, nrepet = 99, ...)
# S3 method for class 'pcaivortho'
randtest(xtest, nrepet = 99, ...)

Arguments

xtest

an object of class pcaiv, pcaivortho or caiv

nrepet

the number of permutations

...

further arguments passed to or from other methods

Value

a list of the class randtest

Author

Stéphane Dray stephane.dray@univ-lyon1.fr, original code by Raphaël Pélissier

Examples

data(rpjdl)
millog <- log(rpjdl$mil + 1)
coa1 <- dudi.coa(rpjdl$fau, scann = FALSE)
caiv1 <- pcaiv(coa1, millog, scan = FALSE)
randtest(caiv1)
#> Monte-Carlo test
#> Call: randtest.pcaiv(xtest = caiv1)
#> 
#> Observation: 0.2520234 
#> 
#> Based on 99 replicates
#> Simulated p-value: 0.01 
#> Alternative hypothesis: greater 
#> 
#>      Std.Obs  Expectation     Variance 
#> 4.269297e+01 4.411699e-02 2.371501e-05