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: |
0.1.1 |
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 gmail.com> |
BugReports: |
https://github.com/tomzylkin/penppml/issues |
License: |
MIT + file LICENSE |
URL: |
https://github.com/tomzylkin/penppml |
NeedsCompilation: |
yes |
Materials: |
README NEWS |
CRAN checks: |
penppml results |
Documentation:
Downloads:
Linking:
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