pca: pca

In wrathematics/fmlr: Fused Matrix Library for R

Description

Perform principal components analysis.

Usage

stats_pca(rm_mean = TRUE, rm_sd = FALSE, x, sdev, rot = NULL)

Arguments

rm_mean, rm_sd	Should the data be centered/scaled first? Operations occur in-place.
x	Input matrix. The input values are overwritten.
sdev	The standard deviations for the principal components.
rot	The pca loadings. If NULL is passed, then these will not be calculated.

Examples

suppressMessages(library(fmlr))
x = cpumat(3, 2)
x$fill_linspace(1, 6)

s = cpuvec()
stats_pca(TRUE, TRUE, x, s)
s$info()
s$print()

wrathematics/fmlr documentation built on Jan. 17, 2022, 4:10 p.m.