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

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

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

ade4 documentation built on Feb. 16, 2023, 7:58 p.m.