schottTest {TestIndVars}

Schott's Test for testing independency

Description

Performs Schott's test for the correlation matrix to assess if the correlation matrix is significantly different from an identity matrix.

Usage

schottTest(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, alpha value, p-value, and test result.

References

Schott, J. R. (2005). Testing for complete independence in high dimensions, Biometrika, 92(4), 951–956.

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
schottTest(data)

# 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
schottTest(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
schottTest(data)