R: Monte-Carlo Test on a Discriminant Analysis (in R).

rtest.discrimin {ade4} | R Documentation

## Monte-Carlo Test on a Discriminant Analysis (in R).

### Description

Test of the sum of a discriminant analysis eigenvalues (divided by the rank). Non parametric version of the Pillai's test. It authorizes any weighting.

### Usage

    ## S3 method for class 'discrimin'
    rtest(xtest, nrepet = 99, ...)

### Arguments

`xtest` | an object of class `discrimin`
`nrepet` | the number of permutations
`...` | further arguments passed to or from other methods

### Value

returns a list of class `rtest`

### Author(s)

Daniel Chessel

### Examples

    data(meaudret)
    pca1 <- dudi.pca(meaudret$env, scan = FALSE, nf = 3)
    rand1 <- rtest(discrimin(pca1, meaudret$design$season, scan = FALSE), 99)
    rand1
    #Monte-Carlo test
    #Observation: 0.3035
    #Call: as.rtest(sim = sim, obs = obs)
    #Based on 999 replicates
    #Simulated p-value: 0.001
    plot(rand1, main = "Monte-Carlo test")
    summary.manova(manova(as.matrix(meaudret$env)~meaudret$design$season), "Pillai")
    #                         Df Pillai approx F num Df den Df  Pr(>F)
    # meaudret$design$season  3   2.73    11.30     27     30 1.6e-09 ***
    # Residuals         16
    # ---
    # Signif. codes:  0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1
    # 2.731/9 = 0.3034

[Package ade4 version 1.7-16 Index]