GulFM (version 0.5.0)

estimate_gul_loadings: General unilateral load Estimator

Description

General unilateral load Estimator

Usage

estimate_gul_loadings(X, m)

Value

A list with hat_A1 : p * m 1st-layer loadings hat_A2 : m * m 2nd-layer loadings hat_Ag : p * m overall loadings Sigma1 : p * p sample cov(X) (for diagnostics) Sigma2 : m * m sample cov(hat_gF1) hat_gF1 : n * m estimated transformed latent factors eig1 : eigen-values of Sigma1 eig2 : eigen-values of Sigma2

Arguments

X

n *p data matrix (already centred and scaled if desired).

m

number of latent factors (both layers).

Details

Step 1: PCA on X to get hat_A1 Step 2: Regress X on hat_A1 to get hat_gF1 Step 3: PCA on hat_gF1 to get hat_A2 Step 4: hat_Ag = hat_A1

Examples

dat  <- generate_gfm_data(500, 50, 5, tanh, seed = 1)
est  <- estimate_gul_loadings(dat$X, m = 5)
err  <- sqrt(mean((est$hat_Ag - dat$Ag)^2))  # overall RMSE