Monte-Carlo test on a Co-inertia analysis (in C).
Performs a Monte-Carlo test on a Co-inertia analysis.
## S3 method for class 'coinertia' randtest(xtest, nrepet = 999, fixed=0, ...)
xtest |
an object of class |
nrepet |
the number of permutations |
fixed |
when non uniform row weights are used in the coinertia analysis, this parameter must be the number of the table that should be kept fixed in the permutations |
... |
further arguments passed to or from other methods |
a list of the class randtest
A testing procedure based on the total coinertia of the analysis
is available by the function randtest.coinertia. The function
allows to deal with various analyses for the two tables. The test is
based on random permutations of the rows of the two tables. If the row
weights are not uniform, mean and variances are recomputed for each
permutation (PCA); for MCA, tables are recentred and column weights are recomputed. If weights are computed using the data contained in one
table (e.g. COA), you must fix this table and permute only the rows of
the other table. The case of decentred PCA (PCA where centers are
entered by the user) is not yet implemented. If you want to use the
testing procedure for this case, you must firstly center the table and then perform a
non-centered PCA on the modified table. The case where one table is
treated by hill-smith analysis (mix of quantitative and qualitative
variables) will be soon implemented.
Jean Thioulouse Jean.Thioulouse@univ-lyon1.fr modified by Stéphane Dray stephane.dray@univ-lyon1.fr
Dolédec, S. and Chessel, D. (1994) Co-inertia analysis: an alternative method for studying species-environment relationships. Freshwater Biology, 31, 277–294.
data(doubs) dudi1 <- dudi.pca(doubs$env, scale = TRUE, scan = FALSE, nf = 3) dudi2 <- dudi.pca(doubs$fish, scale = FALSE, scan = FALSE, nf = 2) coin1 <- coinertia(dudi1,dudi2, scan = FALSE, nf = 2) plot(randtest(coin1))
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