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) < http://hdl.handle.net/10986/35451> and takes advantage of the method of alternating projections of Gaure (2013) for dealing with HDFE, as well as the coordinate descent algorithm of Friedman, Hastie and Tibshirani (2010) 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) .


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("penppml")

0.1.0 by Nicolas Apfel, 15 days ago


https://github.com/tomzylkin/penppml


Report a bug at https://github.com/tomzylkin/penppml/issues


Browse source code at https://github.com/cran/penppml


Authors: Diego Ferreras Garrucho [aut] , Tom Zylkin [aut] , Nicolas Apfel [cre]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports Rcpp, glmnet, lfe, ncvreg, tidyr, rlang, magrittr

Suggests testthat, MASS, knitr, rmarkdown, directlabels, ggplot2, reshape2

Linking to Rcpp, RcppEigen


See at CRAN