kaiserCrit: Selecting the number of principal components to be extracted...

In drclust: Simultaneous Clustering and (or) Dimensionality Reduction

Selecting the number of principal components to be extracted from a dataset

Description

Selects the optimal number of principal components to be extracted from a dataset based on Kaiser's criterion

Usage

kaiserCrit(data)

Arguments

data	Units x variables data matrix.

Value

bestQ

Number of components to be extracted (scalar).

Author(s)

Ionel Prunila, Maurizio Vichi

References

Kaiser H. F. (1960) "The Application of Electronic Computers to Factor Analysis" <doi:10.1177/001316446002000>

Examples

# Iris data 
# Loading the numeric variables of iris data
iris <- scale(as.matrix(iris[,-5])) 

# Apply the Kaiser rule
h <- kaiserCrit(iris)

drclust documentation built on May 29, 2024, 3:51 a.m.