extlasso: Maximum penalized likelihood estimation with extended lasso penalty

The package estimates coefficients of extended LASSO penalized linear regression and generalized linear models. Currently lasso and elastic net penalized linear regression and generalized linear models are considered. The package currently utilizes an accurate approximation of L1 penalty and then a modified Jacobi algorithm to estimate the coefficients. There is provision for plotting of the solutions and predictions of coefficients at given values of lambda. The package also contains functions for cross validation to select a suitable lambda value given the data. The package also provides a function for estimation in fused lasso penalized linear regression.

Getting started

Package details

AuthorB N Mandal <mandal.stat@gmail.com> and Jun Ma <jun.ma@mq.edu.au>
MaintainerB N Mandal <mandal.stat@gmail.com>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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extlasso documentation built on May 2, 2019, 11:39 a.m.