sortinghat (version 0.1)

cov_autocorrelation: Constructs a p-dimensional covariance matrix with an autocorrelation (autoregressive) structure.

Description

This function generates a $p \times p$ autocorrelated covariance matrix with autocorrelation parameter rho. The variance sigma2 is constant for each feature and defaulted to 1.

Usage

cov_autocorrelation(p = 100, rho = 0.9, sigma2 = 1)

Arguments

p

the size of the covariance matrix

rho

the autocorrelation value

sigma2

the variance of each feature

Value

• autocorrelated covariance matrix

Details

The autocorrelated covariance matrix is defined as: The $(i,j)$th entry of the autocorrelated covariance matrix is defined as: $\rho^{|i - j|}$.

The value of rho must be such that $|\rho| < 1$ to ensure that the covariance matrix is positive definite.