PcaClassic {rrcov}R Documentation

Principal Components Analysis

Description

Performs a principal components analysis and returns the results as an object of class PcaClassic (aka constructor).

Usage

PcaClassic(x, ...)
## Default S3 method:
PcaClassic(x, k = 0, kmax = ncol(x), trace=FALSE, ...)
## S3 method for class 'formula':
PcaClassic(formula, data = NULL, subset, na.action, ...)

Arguments

formula a formula with no response variable, referring only to numeric variables.
data an optional data frame (or similar: see model.frame) containing the variables in the formula formula.
subset an optional vector used to select rows (observations) of the data matrix x.
na.action a function which indicates what should happen when the data contain NAs. The default is set by the na.action setting of options, and is na.fail if that is unset. The default is na.omit.
... arguments passed to or from other methods.
x a numeric matrix (or data frame) which provides the data for the principal components analysis.
k number of principal components to compute. If k is missing, or k = 0, the algorithm itself will determine the number of components by finding such k that l_k/l_1 >= 10.E-3 and Σ_{j=1}^k l_j/Σ_{j=1}^r l_j >= 0.8. It is preferable to investigate the scree plot in order to choose the number of components and the run again. Default is k=0.
kmax maximal number of principal components to compute. Default is kmax=10. If k is provided, kmax does not need to be specified, unless k is larger than 10.
trace whether to print intermediate results. Default is trace = FALSE

Value

An S4 object of class PcaClassic-class which is a subclass of the virtual class Pca-class.

Note

This function can be seen as a wrapper arround prcomp() from stats which returns the results of the PCA in a class compatible with the object model for robust PCA.

Author(s)

Valentin Todorov valentin.todorov@chello.at

See Also

Pca-class, PcaClassic-class,


[Package rrcov version 0.5-01 Index]