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>.

Version: 0.1.1
Depends: R (≥ 2.10)
Imports: Rcpp, glmnet, fixest, collapse, rlang, magrittr
LinkingTo: Rcpp, RcppEigen
Suggests: testthat (≥ 3.0.0), MASS, knitr, rmarkdown, directlabels, ggplot2, reshape2
Published: 2022-01-03
Author: Diego Ferreras Garrucho [aut], Tom Zylkin [aut], Nicolas Apfel [cre]
Maintainer: Nicolas Apfel <nicolas.apfel at>
License: MIT + file LICENSE
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: penppml results


Reference manual: penppml.pdf
Vignettes: Penalized PPML Regression with penppml


Package source: penppml_0.1.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): penppml_0.1.1.tgz, r-oldrel (arm64): penppml_0.1.1.tgz, r-release (x86_64): penppml_0.1.1.tgz, r-oldrel (x86_64): penppml_0.1.1.tgz
Old sources: penppml archive


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