neuroconductor/cap: Covariate Assisted Principal (CAP) Regression for Covariance Matrix Outcomes

Performs Covariate Assisted Principal (CAP) Regression for covariance matrix outcomes. The method identifies the optimal projection direction which maximizes the log-likelihood function of the log-linear heteroscedastic regression model in the projection space. See Zhao et al. (2018), Covariate Assisted Principal Regression for Covariance Matrix Outcomes, <doi:10.1101/425033> for details.

Getting started

Package details

AuthorYi Zhao <[email protected]>, Bingkai Wang <[email protected]>, Stewart Mostofsky <[email protected]>, Brian Caffo <[email protected]>, Xi Luo <[email protected]>
MaintainerYi Zhao <[email protected]>
LicenseGPL (>=2)
Version1.0
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("neuroconductor/cap")
neuroconductor/cap documentation built on May 17, 2019, 12:03 p.m.