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.

Version:	1.0
Depends:	MASS, multigroup
Published:	2018-09-30
Author:	Yi Zhao, Bingkai Wang, Stewart Mostofsky, Brian Caffo, Xi Luo
Maintainer:	Yi Zhao <zhaoyi1026 at gmail.com>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	no
CRAN checks:	cap results

Documentation:

Reference manual:

cap.pdf

Downloads:

Package source:	cap_1.0.tar.gz
Windows binaries:	r-devel: cap_1.0.zip, r-release: cap_1.0.zip, r-oldrel: cap_1.0.zip
macOS binaries:	r-release (arm64): cap_1.0.tgz, r-oldrel (arm64): cap_1.0.tgz, r-release (x86_64): cap_1.0.tgz, r-oldrel (x86_64): cap_1.0.tgz

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