pca_eigen {booklet} | R Documentation |
Compute eigenvalues and eigenvectors
Description
Return eigenvalues and eigenvectors of a matrix
Usage
pca_eigen(X)
pca_weighted_eigen(
X,
weighted_row = rep(1, nrow(X))/nrow(X),
weighted_col = rep(1, ncol(X))
)
Arguments
X |
X_active |
weighted_row |
row weights |
weighted_col |
column weights |
Details
Standardization depends on what you need to perform factor analysis. We implemented two types:
-
pca_weighted_eigen
: This is the default method in FactoMineR to compute eigvalues, eigvectors and U matrix. -
pca_eigen
: This is the standard method to compute eigenvalues, eigenvectors.
Value
A list containing results of Single Value Decomposition (SVD).
Examples
library(booklet)
iris[, -5] |>
pca_standardize_norm() |>
pca_eigen()
[Package booklet version 1.0.0 Index]