rotate.pca: Rotate PCA Loadings

In bbuchsbaum/multivarious: Extensible Data Structures for Multivariate Analysis

Rotate PCA Loadings

Description

Apply a specified rotation to the component loadings of a PCA model. This function leverages the GPArotation package to apply orthogonal or oblique rotations.

Usage

## S3 method for class 'pca'
rotate(
  x,
  ncomp,
  type = c("varimax", "quartimax", "promax"),
  loadings_type = c("pattern", "structure"),
  score_method = c("auto", "recompute", "original"),
  ...
)

Arguments

x	A PCA model object, typically created using the pca() function.
ncomp	The number of components to rotate. Must be <= ncomp(x).
type	The type of rotation to apply. Supported rotation types: "varimax" Orthogonal Varimax rotation "quartimax" Orthogonal Quartimax rotation "promax" Oblique Promax rotation
...	Additional arguments passed to GPArotation functions.

Value

A modified PCA object with class rotated_pca and additional fields:

v	Rotated loadings
s	Rotated scores
sdev	Updated standard deviations of rotated components
explained_variance	Proportion of explained variance for each rotated component
rotation	A list with rotation details: type, R (orth) or Phi (oblique), and loadings_type

Examples

# Perform PCA on iris dataset
data(iris)
X <- as.matrix(iris[,1:4])
res <- pca(X, ncomp=4)

# Apply varimax rotation to the first 3 components
rotated_res <- rotate(res, ncomp=3, type="varimax")

bbuchsbaum/multivarious documentation built on Dec. 23, 2024, 7:47 a.m.