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:
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