cernn: Covariance Estimation Regularized by Nuclear Norm Penalties

An implementation of the covariance estimation method proposed in Chi and Lange (2014), "Stable estimation of a covariance matrix guided by nuclear norm penalties," Computational Statistics and Data Analysis 80:117-128.

Author
Eric C. Chi <ecchi1105@gmail.com>
Date of publication
2015-04-15 12:38:20
Maintainer
Eric C. Chi <ecchi1105@gmail.com>
License
MIT + file LICENSE
Version
0.1

View on CRAN

Man pages

cernn
Compute the regularization path for Covariance Estimate...
get_alpha
Compute alpha parameter for covariance regularization.
get_lambda_max
Compute lambda_max parameter for covariance regularization.
loss_entropy
Entropy Loss
loss_quadratic
Quadratic Loss
select_lambda
Selection of penalty parameter based on cross-validation
shrink_eigen
Nonlinear shrinkage of sample eigenvalues

Files in this package

cernn
cernn/inst
cernn/inst/CITATION
cernn/NAMESPACE
cernn/R
cernn/R/cernn.r
cernn/MD5
cernn/DESCRIPTION
cernn/man
cernn/man/get_lambda_max.Rd
cernn/man/get_alpha.Rd
cernn/man/cernn.Rd
cernn/man/loss_quadratic.Rd
cernn/man/shrink_eigen.Rd
cernn/man/select_lambda.Rd
cernn/man/loss_entropy.Rd
cernn/LICENSE