# rtest.discrimin: Monte-Carlo Test on a Discriminant Analysis (in R). In ade4: Analysis of Ecological Data: Exploratory and Euclidean Methods in Environmental Sciences

 rtest.discrimin 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`

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
```

ade4 documentation built on Nov. 2, 2022, 1:07 a.m.