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.

Install the latest version of this package by entering the following in R:

`install.packages("cernn")`

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 |

**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

inst

inst/CITATION

NAMESPACE

R

R/cernn.r
MD5

DESCRIPTION

man

man/get_lambda_max.Rd
man/get_alpha.Rd
man/cernn.Rd
man/loss_quadratic.Rd
man/shrink_eigen.Rd
man/select_lambda.Rd
man/loss_entropy.Rd
LICENSE

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Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.

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