This function implements the Random Covariance Model (RCM) for joint estimation of
multiple sparse precision matrices. Optimization is conducted using block
coordinate descent.
Usage
spcov_bcd(samp_cov, rho, initial = NULL)
Arguments
- samp_cov
\(p\) x \(p\) sample covariance matrix.
- rho
Non-negative scalar. Induces sparsity in covariance matrix.
- initial
Initial value for covariance matrix.
Value
\(p\) x \(p\) sparse covariance matrix estimate.
References
Wang, Hao.
"Two New Algorithms for Solving Covariance Graphical Lasso Based on Coordinate Descent and ECM." 2012. https://arxiv.org/pdf/1205.4120.pdf