Fit a Single PCA (Ignoring Clusters)

Concatenates all data into one matrix, performs SVD, keeps r principal components, then computes a naive PPCA logLik and BIC.

Usage

fit_single_pca(list_of_data, r = 2)

Arguments

list_of_data

List of (T_i x M) matrices.

r

Number of principal components.

Value

A list with (P, mu, sigma2, logLik, BIC).

Examples

if (FALSE) { # \dontrun{
sim <- simulate_mixture_data(N = 50, K = 3, r = 2, M = 6, T_each = 100)
pca_res <- fit_single_pca(sim$list_of_data, r = 2)
print(pca_res$BIC)
} # }