calcPCA: Calculate PCA and associated statistics.

In MiguelRodo/ggboot: Bootstrap univariate and multivariate plots

Calculate PCA and associated statistics.

Description

Calculate PCA

Usage

calcPCA(grid, centre = TRUE, scale, r = ncol(grid))

Arguments

grid	matrix or dataframe. If a dataframe, then the numeric columns are selected and converted to a matrix.
centre, scale	logical. If TRUE, then the matrix has its mean subtracted (centre) and/or has each column divided by its sd (scale). If scale = TRUE and the sd of a column is 0, then that column is not divided by its sd and a message is printed.
r	integer. The number of principal compononents to show information for. Defaults to ncol(grid).

Value

A list containing elements:

VJMat	matrix of eigenvectors
YMat	matrix of principal component scores
singValVec	vector of singular values
cumPropVarVec	vector of cumulative proportion of variation
compPropVarVec	vector of component-wise proportion of variation

MiguelRodo/ggboot documentation built on Nov. 9, 2023, 5:45 p.m.