penppml: Penalized Poisson Pseudo Maximum Likelihood Regression

A set of tools that enables efficient estimation of penalized Poisson Pseudo Maximum Likelihood regressions, using lasso or ridge penalties, for models that feature one or more sets of high-dimensional fixed effects. The methodology is based on Breinlich, Corradi, Rocha, Ruta, Santos Silva, and Zylkin (2021) <> and takes advantage of the method of alternating projections of Gaure (2013) <doi:10.1016/j.csda.2013.03.024> for dealing with HDFE, as well as the coordinate descent algorithm of Friedman, Hastie and Tibshirani (2010) <doi:10.18637/jss.v033.i01> for fitting lasso regressions. The package is also able to carry out cross-validation and to implement the plugin lasso of Belloni, Chernozhukov, Hansen and Kozbur (2016) <doi:10.1080/07350015.2015.1102733>.

Package details

AuthorDiego Ferreras Garrucho [aut], Tom Zylkin [aut], Nicolas Apfel [cre]
MaintainerNicolas Apfel <>
LicenseMIT + file LICENSE
Package repositoryView on CRAN
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penppml documentation built on Sept. 9, 2021, 9:09 a.m.