Principal component analysis {Rfast2}

Principal component analysis

Description

Principal component analysis.

Usage

pca(x, center = TRUE, scale = TRUE, k = NULL, vectors = FALSE)

Arguments

x

A numerical n \times p matrix with data where the rows are the observations and the columns are the variables.

center

Do you want your data centered? TRUE or FALSE.

scale

Do you want each of your variables scaled, i.e. to have unit variance? TRUE or FALSE.

k

If you want a specific number of eigenvalues and eigenvectors set it here, otherwise all eigenvalues (and eigenvectors if requested) will be returned.

vectors

Do you want the eigenvectors be returned? By dafault this is FALSE.

Details

The function is a faster version of R's prcomp.

Value

A list including:

values

The eigenvalues.

vectors

The eigenvectors.

Author(s)

Michail Tsagris.

R implementation and documentation: Michail Tsagris [e-mail].

See Also

reg.mle.lda

Examples

x <- matrix( rnorm(1000 * 20 ), ncol = 20)
a <- pca(x)
x <- NULL