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.
|Author||Yi Zhao <[email protected]>, Bingkai Wang <[email protected]>, Stewart Mostofsky <[email protected]>, Brian Caffo <[email protected]>, Xi Luo <[email protected]>|
|Maintainer||Yi Zhao <[email protected]>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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