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

In ade4: Analysis of Ecological Data : Exploratory and Euclidean Methods in Environmental Sciences

Description

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

Value

a list of the class randtest

Author(s)

Jean Thioulouse [e-mail]

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.

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)

Example output

Monte-Carlo test
Call: randtest.coinertia(xtest = res, nrepet = nrepet)

Observation: 0.8204725 

Based on 999 replicates
Simulated p-value: 0.004 
Alternative hypothesis: greater 

    Std.Obs Expectation    Variance 
 2.69895880  0.50055243  0.01405045 

ade4 documentation built on May 2, 2019, 5:50 p.m.