lrTest: Likelihood Ratio Test for Covariance Matrix

In TestIndVars: Testing the Independence of Variables for Specific Covariance Structures

Likelihood Ratio Test for Covariance Matrix

Description

Performs a likelihood ratio test for the covariance matrix to assess if the covariance matrix is significantly different from an identity matrix.

Usage

lrTest(X, alpha = 0.05)

Arguments

X	A numeric matrix or data frame containing the variables.
alpha	The significance level for the test. (default is 0.05).

Value

A data frame containing the test statistic, degrees of freedom, critical value, p-value, and test result.

Examples

library(MASS)

n = 50 # Sample Size
p = 5
rho = 0.1

# Building a Covariance structure with Autoregressive structure
cov_mat <- covMatAR(p = p, rho = rho)
# Simulated data
data <- mvrnorm(n = n, mu = rep(0,p), Sigma = cov_mat)
# Performing the test
lrTest(data, alpha = 0.01)

# Building a Covariance structure with Compound Symmetry structure
cov_mat <- covMatCS(p = p, rho = rho)
# Simulated data
data <- mvrnorm(n = n, mu = rep(0,p), Sigma = cov_mat)
# Performing the test
lrTest(data)

# Building a Covariance structure with Circular structure
cov_mat <- covMatC(p = p, rho = rho)
# Simulated data
data <- mvrnorm(n = n, mu = rep(0,p), Sigma = cov_mat)
# Performing the test
lrTest(data)

TestIndVars documentation built on May 29, 2024, 6:14 a.m.