mca_bootstrap: Bootstrap-Based Subspace Stability Assessment

In alsi: Aggregated Latent Space Index for Multiple Correspondence Analysis

Bootstrap-Based Subspace Stability Assessment

Description

Evaluates reproducibility of retained MCA dimensions via bootstrap resampling. Quantifies stability using Procrustes principal angles (subspace-level) and Tucker's congruence coefficients (dimension-level).

Usage

mca_bootstrap(data, vars, K, B = 2000, seed = 20260123, verbose = TRUE)

Arguments

data	Data frame or path to .xlsx file
vars	Character vector of binary variable names
K	Integer, number of dimensions to retain and assess
B	Integer, number of bootstrap resamples (default: 2000)
seed	Integer, random seed for reproducibility
verbose	Logical, print progress messages

Value

S3 object of class mca_bootstrap containing:

ref	Reference MCA fit
K	Number of dimensions assessed
B	Number of bootstrap resamples
angles	Matrix of principal angles (B \times K)
tucker	Matrix of Tucker congruence coefficients (B \times K)
angles_summary	Summary statistics for angles
tucker_summary	Summary statistics for congruence

Examples

data(ANR2)
boot <- mca_bootstrap(ANR2, vars = names(ANR2), K = 3, B = 100)
print(boot)
plot(boot)

alsi documentation built on Feb. 17, 2026, 5:07 p.m.