calculate_errors: calculate_errors Function

In SFM: A Package for Analyzing Skew Factor Models

calculate_errors Function

Description

This function calculates the Mean Squared Error (MSE) and relative error for factor loadings and uniqueness estimates obtained from factor analysis.

Usage

calculate_errors(data, A, D)

Arguments

data	Matrix of SFM data.
A	Matrix of true factor loadings.
D	Matrix of true uniquenesses.

Value

A named vector containing:

MSEA	Mean Squared Error for factor loadings.
MSED	Mean Squared Error for uniqueness estimates.
LSA	Relative error for factor loadings.
LSD	Relative error for uniqueness estimates.

Examples

set.seed(123) # For reproducibility
# Define dimensions
n <- 10  # Number of samples
p <- 5   # Number of factors

# Generate matrices with compatible dimensions
A <- matrix(runif(p * p, -1, 1), nrow = p)  # Factor loadings matrix (p x p)
D <- diag(runif(p, 1, 2))  # Uniquenesses matrix (p x p)
data <- matrix(runif(n * p), nrow = n)  # Data matrix (n x p)

# Calculate errors
errors <- calculate_errors(data, A, D)
print(errors)

SFM documentation built on April 15, 2025, 5:09 p.m.