testdim: Function to perform a test of dimensionality

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

Function to perform a test of dimensionality

Description

This functions allow to test for the number of axes in multivariate analysis. The procedure testdim.pca implements a method for principal component analysis on correlation matrix. The procedure is based on the computation of the RV coefficient.

Usage

testdim(object, ...)
## S3 method for class 'pca'
testdim(object, nrepet = 99, nbax = object$rank, alpha = 0.05, ...)

Arguments

object	an object corresponding to an analysis (e.g. duality diagram, an object of class dudi)
nrepet	the number of repetitions for the permutation procedure
nbax	the number of axes to be tested, by default all axes
alpha	the significance level
...	other arguments

Value

An object of the class krandtest. It contains also:

nb	The estimated number of axes to keep
nb.cor	The number of axes to keep estimated using a sequential Bonferroni procedure

Author(s)

Stéphane Dray [e-mail]

References

Dray, S. (2008) On the number of principal components: A test of dimensionality based on measurements of similarity between matrices. Computational Statistics and Data Analysis, Volume 52, 2228–2237. doi:10.1016/j.csda.2007.07.015

See Also

dudi.pca, RV.rtest,testdim.multiblock

Examples

tab <- data.frame(matrix(rnorm(200),20,10))
pca1 <- dudi.pca(tab,scannf=FALSE)
test1 <- testdim(pca1)
test1
test1$nb
test1$nb.cor
data(doubs)
pca2 <- dudi.pca(doubs$env,scannf=FALSE)
test2 <- testdim(pca2)
test2
test2$nb
test2$nb.cor

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