procuste.randtest {ade4}R Documentation

Monte-Carlo Test on the sum of the singular values of a procustean rotation (in C).

Description

performs a Monte-Carlo Test on the sum of the singular values of a procustean rotation.

Usage

procuste.randtest(df1, df2, nrepet = 999)

Arguments

df1 a data frame
df2 a data frame
nrepet the number of permutations

Value

returns a list of class randtest

Author(s)

Jean Thioulouse ade4-jt@biomserv.univ-lyon1.fr

References

Jackson, D.A. (1995) PROTEST: a PROcustean randomization TEST of community environment concordance. Ecosciences, 2, 297–303.

Examples

data(doubs)
pca1 <- dudi.pca(doubs$mil, scal = TRUE, scann = FALSE)
pca2 <- dudi.pca(doubs$poi, scal = FALSE, scann = FALSE)
protest1 <- procuste.randtest(pca1$tab, pca2$tab, 999)
protest1
plot(protest1,main="PROTEST")

Worked out examples


> library(ade4)
> ### Name: procuste.randtest
> ### Title: Monte-Carlo Test on the sum of the singular values of a
> ###   procustean rotation (in C).
> ### Aliases: procuste.randtest
> ### Keywords: multivariate nonparametric
> 
> ### ** Examples
> 
> data(doubs)
> pca1 <- dudi.pca(doubs$mil, scal = TRUE, scann = FALSE)
> pca2 <- dudi.pca(doubs$poi, scal = FALSE, scann = FALSE)
> protest1 <- procuste.randtest(pca1$tab, pca2$tab, 999)
> protest1
Monte-Carlo test
Call: procuste.randtest(df1 = pca1$tab, df2 = pca2$tab, nrepet = 999)

Observation: 0.6562 

Based on 999 replicates
Simulated p-value: 0.001 
Alternative hypothesis: greater 

    Std.Obs Expectation    Variance 
6.584401804 0.342097252 0.002275678 
> plot(protest1,main="PROTEST")
> 
> 
> 
> 

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