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) <http://hdl.handle.net/10986/35451> 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:	0.2.3
Depends:	R (≥ 2.10)
Imports:	Rcpp, glmnet, fixest, collapse, rlang, magrittr, matrixStats, dplyr, devtools
LinkingTo:	Rcpp, RcppEigen
Suggests:	testthat (≥ 3.0.0), MASS, knitr, rmarkdown, ggplot2, reshape2
Published:	2023-09-08
Author:	Diego Ferreras Garrucho [aut], Tom Zylkin [aut], Joao Cruz [cre], Nicolas Apfel [ctb]
Maintainer:	Joao Cruz <jm01780 at surrey.ac.uk>
BugReports:	https://github.com/tomzylkin/penppml/issues
License:	MIT + file LICENSE
URL:	https://github.com/tomzylkin/penppml
NeedsCompilation:	yes
Materials:	README NEWS
In views:	Econometrics
CRAN checks:	penppml results

Documentation:

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

Downloads:

Package source:	penppml_0.2.3.tar.gz
Windows binaries:	r-devel: penppml_0.2.3.zip, r-release: penppml_0.2.3.zip, r-oldrel: penppml_0.2.3.zip
macOS binaries:	r-release (arm64): penppml_0.2.3.tgz, r-oldrel (arm64): penppml_0.2.3.tgz, r-release (x86_64): penppml_0.2.3.tgz, r-oldrel (x86_64): penppml_0.2.3.tgz
Old sources:	penppml archive

Linking:

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