Description Author(s) References
cap package 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.
Yi Zhao, Johns Hopkins University, <zhaoyi1026@gmail.com>
Bingkai Wang, Johns Hopkins University, <bwang51@jhmi.edu>
Stewart Mostofsky, Johns Hopkins University, <mostofsky@kennedykrieger.org>
Brian Caffo, Johns Hopkins University, <bcaffo@gmail.com>
Xi Luo, Brown University, <xi.rossi.luo@gmail.com>
Maintainer: Yi Zhao <zhaoyi1026@gmail.com>
Zhao et al. (2018) Covariate Assisted Principal Regression for Covariance Matrix Outcomes <doi:10.1101/425033>
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