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, for details.


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install.packages("cap")

1.0 by Yi Zhao, 7 months ago


Browse source code at https://github.com/cran/cap


Authors: Yi Zhao <[email protected]> , Bingkai Wang <[email protected]> , Stewart Mostofsky <[email protected]> , Brian Caffo <[email protected]> , Xi Luo <[email protected]>


Documentation:   PDF Manual  


GPL (>= 2) license


Depends on MASS, multigroup


See at CRAN