cov_autocorrelation: Constructs a p-dimensional covariance matrix with an...

In ramhiser/sortinghat: sortinghat

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

Details

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

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

Value

autocorrelated covariance matrix

ramhiser/sortinghat documentation built on May 26, 2019, 10:12 p.m.