RCOV: Regularized Covariance Matrix Calculation

In ssMRCD: Robust Estimators for Multi-Group and Spatial Data

Regularized Covariance Matrix Calculation

Description

Computes a regularized covariance matrix using a convex combination of a target matrix and the sample covariance matrix.

Arguments

XX	A numeric matrix containing the observations, where each column represents a different observation.
vMu	A numeric vector representing the mean vector to center the columns of XX.
rho	A numeric scalar representing the regularization parameter (between 0 and 1) that balances between the target matrix and the sample covariance.
mT	A numeric matrix representing the target covariance matrix for regularization.
scfac	A numeric scalar representing a scaling factor applied to the sample covariance matrix.

Details

The function calculates the sample covariance matrix of the centered data XX and combines it with the target covariance matrix mT, scaled by the factor scfac. The regularization is controlled by the parameter rho, where rho = 1 results in using only the target matrix, and rho = 0 uses only the sample covariance.

Value

A named list containing:

rho	The regularization parameter used in the calculation.
mT	The target covariance matrix provided as input.
cov	The sample covariance matrix calculated from the centered observations.
rcov	The regularized covariance matrix, which is a convex combination of the target matrix and scaled sample covariance matrix.

ssMRCD documentation built on Nov. 5, 2025, 7:44 p.m.