PCA: A Principal Components Analysis tool based on single value...

In IsaacShaffer/PCAtools: What the Package Does (One Line, Title Case)

Description

A Principal Components Analysis tool based on single value decomposition

Usage

PCA(data, scale = FALSE)

Arguments

data	An N x P matrix of N observations on P features.
scale	If TRUE features are scaled AND centered. If FALSE features are only centered. default: FALSE

Examples

PCA.model <- PCA(iris[,1:4])

IsaacShaffer/PCAtools documentation built on Dec. 31, 2020, 1:06 p.m.