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cernn (version 0.1)

Covariance Estimation Regularized by Nuclear Norm Penalties

Description

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.

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Version

Install

install.packages('cernn')

Monthly Downloads

20

Version

0.1

License

MIT + file LICENSE

Maintainer

Eric Chi

Last Published

April 15th, 2015

Functions in cernn (0.1)

get_lambda_max

Compute lambda_max parameter for covariance regularization.
get_alpha

Compute alpha parameter for covariance regularization.
shrink_eigen

Nonlinear shrinkage of sample eigenvalues
loss_entropy

Entropy Loss
loss_quadratic

Quadratic Loss
cernn

Compute the regularization path for Covariance Estimate Regularized by Nuclear Norms (CERNN)
select_lambda

Selection of penalty parameter based on cross-validation