Monte-Carlo test on a Costatis analysis (in C).

Performs a Monte-Carlo test on a Costatis analysis.

Usage

costatis.randtest(KTX, KTY, nrepet = 999, ...)

Arguments

KTX

an objet of class ktab

KTY

an objet of class ktab

nrepet

the number of permutations

...

further arguments passed to or from other methods

Value

a list of the class randtest

References

Thioulouse J. (2011). Simultaneous analysis of a sequence of paired ecological tables: a comparison of several methods. Annals of Applied Statistics, 5, 2300-2325.

Author

Jean Thioulouse Jean.Thioulouse@univ-lyon1.fr

Examples

data(meau)
wit1 <- withinpca(meau$env, meau$design$season, scan = FALSE, scal = "total")
pcaspe <- dudi.pca(meau$spe, scale = FALSE, scan = FALSE, nf = 2)
wit2 <- wca(pcaspe, meau$design$season, scan = FALSE, nf = 2)
kta1 <- ktab.within(wit1, colnames = rep(c("S1","S2","S3","S4","S5","S6"), 4))
kta2 <- ktab.within(wit2, colnames = rep(c("S1","S2","S3","S4","S5","S6"), 4))
costatis1 <- costatis(kta1, kta2, scan = FALSE)
costatis.randtest(kta1, kta2)
#> Monte-Carlo test
#> Call: randtest.coinertia(xtest = res, nrepet = nrepet)
#> 
#> Observation: 0.8204725 
#> 
#> Based on 999 replicates
#> Simulated p-value: 0.006 
#> Alternative hypothesis: greater 
#> 
#>     Std.Obs Expectation    Variance 
#>  2.80235653  0.49209258  0.01373113