run pca

Given a matrix of values, runs principal component analysis (PCA) using prcomp.

Usage

visqc_run_pca(data_matrix, center = TRUE, scale = FALSE, ...)

Arguments

data_matrix

matrix of values

center

should the data be centered (TRUE)

scale

should the data be scaled to unit variance (FALSE)

...

other arguments to prcomp

Value

visqc_run_pca returns a list containing

scores

a data.frame of scores, each column is a principal component.

loadings

a data.frame of the loadings, each column is a principal component.

variances

a data.frame of variance information, each row is a principal component.

Details

runs PCA via prcomp, turns the scores into a data.frame, labelled with their percent variance contribution if labelled is available, and returns the scores, the loadings, and the variance contributions.

See also

stats::prcomp