alsi: Compute Aggregated Latent Space Index (ALSI)

In alsi: Aggregated Latent Space Index for Multiple Correspondence Analysis

Compute Aggregated Latent Space Index (ALSI)

Description

Calculates ALSI as a variance-weighted Euclidean norm of row principal coordinates within a retained K-dimensional MCA subspace.

Usage

alsi(Fmat, eig, K)

Arguments

Fmat	Matrix of row principal coordinates (N \times K or larger)
eig	Vector of eigenvalues (inertias)
K	Integer, number of dimensions to aggregate

Value

S3 object of class alsi containing:

alpha	Numeric vector of ALSI values (length N), representing each individual's variance-weighted distance from the centroid in the retained MCA subspace
w	Variance weights (length K), computed as the proportion of retained inertia for each dimension
alpha_vec	Aggregated direction vector (length K), equal to sqrt(w), used for projecting category coordinates
K	Number of dimensions used in aggregation

Examples

# Create example data
set.seed(123)
Fmat <- matrix(rnorm(100 * 4), nrow = 100, ncol = 4)
eig <- c(0.5, 0.3, 0.15, 0.05)

# Compute ALSI
a <- alsi(Fmat, eig, K = 3)
print(a)
hist(a$alpha, main = "Distribution of ALSI")

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