This repository hosts an R package that implements the methodology developed in "Homogeneity tests of covariance matrices with high-dimensional longitudinal data". That paper considers detecting and identifying change points among covariances of high-dimensional longitudinal data, where the number of features is greater than both the sample size and the number of repeated measurements. The proposed methods are applicable under general temporospatial dependence.
Package HDCovMatTest can be installed using the devtools package in R. Below is R code to obtain HDCovMatTest.
# install (if not available) and load the devtools package
if(!require(devtools)){
install.packages("devtools")
library(devtools)
}
# install HDCovMatTest
install_github("shawnsanto/HDCovMatTest")
# load HDCovMatTest
library(HDCovMatTest)
Zhong, Li, and Santo (2018). Homogeneity tests of covariance matrices with high-dimensional longitudinal data. Biometrika.