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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 |
| Reference manual: | cap.pdf |
| 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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These binaries (installable software) and packages are in development.
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