Joint Mean and Covariance Estimation for Matrix-Variate Data
Center Each Column By Subtracting Group or Global GLS Mean
Center Each Column by Subtracting Group Means
Center Each Column Based on Model Selection
Estimate Row-Row Covariance Structure Using Gemini
Estimate Row-Row Covariance Using Gemini for a Sequence of Penalties
Generalized Least Squares
Estimate Mean and Row-Row Correlation Matrix Using Group Centering
Estimate Mean and Row-Row Correlation Matrix Using Model Selection
Estimate Mean and Correlation Structure Using Stability Selection
Quantile Plot of Test Statistics
Summary of Test Statistics
Penalty Parameter for Covariance Estimation Based on Theory
Penalty Parameter for Covariance Estimation Based on Theory
Design Matrix for Two-Group Mean Estimation
Jointly estimates two-group means and covariances for matrix-variate data and calculates test statistics. This package implements the algorithms defined in Hornstein, Fan, Shedden, and Zhou (2018) <doi:10.1080/01621459.2018.1429275>.