bootstrap.pca: PCA Bootstrap Resampling

In bbuchsbaum/multivarious: Extensible Data Structures for Multivariate Analysis

PCA Bootstrap Resampling

Description

Perform bootstrap resampling for Principal Component Analysis (PCA) to estimate component and score variability.

Usage

## S3 method for class 'pca'
bootstrap(x, nboot = 100, k = ncomp(x), ...)

Arguments

x	A fitted PCA model object.
nboot	The number of bootstrap resamples (default: 100).
k	The number of components to bootstrap (default: all components in the fitted PCA model).
...	Additional arguments to be passed to the specific model implementation of bootstrap.

Value

A list containing bootstrap z-scores for the loadings (zboot_loadings) and scores (zboot_scores).

References

Fisher, Aaron, Brian Caffo, Brian Schwartz, and Vadim Zipunnikov. 2016. "Fast, Exact Bootstrap Principal Component Analysis for P > 1 Million." Journal of the American Statistical Association 111 (514): 846-60.

Examples

X <- matrix(rnorm(10*100), 10, 100)
x <- pca(X, ncomp=9)
bootstrap_results <- bootstrap(x)

bbuchsbaum/multivarious documentation built on April 15, 2024, 3:33 a.m.