Monte-Carlo Test on the percentage of explained (i.e. constrained) inertia
randtest.pcaiv.Rd
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.
Arguments
- xtest
an object of class
pcaiv
,pcaivortho
orcaiv
- nrepet
the number of permutations
- ...
further arguments passed to or from other methods
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