Package cap details

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, for details.

Maintainer: Yi Zhao < zhaoyi1026 at gmail.com >

Documentation

From within R, enter citation('cap')

To cite package 'cap' in publications use:

Yi Zhao, Bingkai Wang, Stewart Mostofsky, Brian Caffo and Xi Luo
(2018). cap: Covariate Assisted Principal (CAP) Regression for
Covariance Matrix Outcomes. R package version 1.0.

A BibTeX entry for LaTeX users is

@Manual{,
title = {cap: Covariate Assisted Principal (CAP) Regression for Covariance Matrix Outcomes},
author = {Yi Zhao and Bingkai Wang and Stewart Mostofsky and Brian Caffo and Xi Luo},
year = {2018},
note = {R package version 1.0},
}

If you have any problems with this package you can open a new issue or check the already existing ones here.

To install this package, start R and enter:

source("https://neuroconductor.org/neurocLite.R")

# Default Install
neuro_install('cap')

# from GitHub
neuro_install('cap', release = "stable", release_repo = "github")
neuro_install('cap', release = "current", release_repo = "github")

More detailed installation instructions can be found here.