# testdim: Function to perform a test of dimensionality In ade4: Analysis of Ecological Data: Exploratory and Euclidean Methods in Environmental Sciences

 testdim R Documentation

## 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 stephane.dray@univ-lyon1.fr

### 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

`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.