Science Score: 23.0%
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Low similarity (16.5%) to scientific vocabulary
Last synced: 11 months ago
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Repository
Penalized Poisson Pseudo Maximum Likelihood
Basic Info
- Host: GitHub
- Owner: tomzylkin
- License: other
- Language: R
- Default Branch: master
- Size: 9.38 MB
Statistics
- Stars: 12
- Watchers: 5
- Forks: 6
- Open Issues: 2
- Releases: 1
Created almost 5 years ago
· Last pushed over 1 year ago
Metadata Files
Readme
Changelog
License
README.Rmd
---
output: github_document
---
```{r, include = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# penppml
The `penppml` package is a set of tools that enables efficient estimation of penalized Poisson Pseudo Maximum Likelihood (PPML) regressions, using lasso or ridge penalties, for models that feature one or more sets of high-dimensional fixed effects (HDFE). The methodology is based on Breinlich, Corradi, Rocha, Ruta, Santos Silva, and Zylkin (2021) and takes advantage of the method of alternating projections of Gaure (2013) for dealing with HDFE, as well as the coordinate descent algorithm of Friedman, Hastie and Tibshirani (2010) for fitting lasso regressions. The package is also able to carry out cross-validation and to implement the plugin lasso of Belloni, Chernozhukov, Hansen and Kozbur (2016).
## Installation
You can install the released version of penppml from [CRAN](https://CRAN.R-project.org) with:
``` r
install.packages("penppml")
```
And the development version from [GitHub](https://github.com/) with:
``` r
# install.packages("devtools")
devtools::install_github("diegoferrerasg/penppml")
```
## Example
This is a basic example which demonstrate how to estimate a gravity model of international trade with three sets of HDFE using the package:
```{r example}
# Setup:
library(penppml)
selected <- countries$iso[countries$region %in% c("Americas")]
trade2 <- trade[(trade$exp %in% selected) & (trade$imp %in% selected), -(5:6)]
lambdas <- c(0.05, 0.025, 0.01, 0.0075, 0.005, 0.0025, 0.001, 0.00075, 0.0005, 0.00025, 0.0001, 0)
```
```{r try mlfitpenppml lasso, results = FALSE}
# Main command:
reg <- mlfitppml(data = trade2,
dep = "export",
fixed = list(c("exp", "time"),
c("imp", "time"),
c("exp", "imp")),
penalty = "lasso",
lambdas = lambdas)
```
For more examples and details on how to use the package, see the vignette.
## References
Breinlich, H., Corradi, V., Rocha, N., Ruta, M., Santos Silva, J.M.C. and T. Zylkin, T. (2021). "Machine Learning in International Trade Research: Evaluating the Impact of Trade Agreements", Policy Research Working Paper; No. 9629. World Bank, Washington, DC.
Correia, S., P. Guimaraes and T. Zylkin (2020). "Fast Poisson estimation with high dimensional fixed effects", *STATA Journal*, 20, 90-115.
Gaure, S (2013). "OLS with multiple high dimensional category variables", *Computational Statistics & Data Analysis*, 66, 8-18.
Friedman, J., T. Hastie, and R. Tibshirani (2010). "Regularization paths for generalized linear models via coordinate descent", *Journal of Statistical Software*, 33, 1-22.
Belloni, A., V. Chernozhukov, C. Hansen and D. Kozbur (2016). "Inference in high dimensional panel models with an application to gun control", *Journal of Business & Economic Statistics*, 34, 590-605.
GitHub Events
Total
- Watch event: 1
- Push event: 2
- Fork event: 1
Last Year
- Watch event: 1
- Push event: 2
- Fork event: 1
Committers
Last synced: over 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| Diego Ferreras Garrucho | d****o@l****k | 75 |
| nicolasapfel | n****l@g****m | 39 |
| tomzylkin | t****n@g****m | 10 |
| jm01780 | j****0@s****k | 10 |
| nicolasapfel | 7****l | 6 |
Committer Domains (Top 20 + Academic)
surrey.ac.uk: 1
lse.ac.uk: 1
Issues and Pull Requests
Last synced: 11 months ago
All Time
- Total issues: 2
- Total pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Total issue authors: 2
- Total pull request authors: 0
- Average comments per issue: 0.5
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- tdhock (1)
- philipocalito (1)
Pull Request Authors
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- cran 351 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 7
- Total maintainers: 1
cran.r-project.org: penppml
Penalized Poisson Pseudo Maximum Likelihood Regression
- Homepage: https://github.com/tomzylkin/penppml
- Documentation: http://cran.r-project.org/web/packages/penppml/penppml.pdf
- License: MIT + file LICENSE
-
Latest release: 0.2.4
published over 1 year ago
Rankings
Forks count: 9.1%
Stargazers count: 19.8%
Average: 29.0%
Dependent packages count: 29.8%
Dependent repos count: 35.5%
Downloads: 50.9%
Maintainers (1)
Last synced:
11 months ago
Dependencies
DESCRIPTION
cran
- R >= 2.10 depends
- Rcpp * imports
- collapse * imports
- fixest * imports
- glmnet * imports
- magrittr * imports
- rlang * imports
- MASS * suggests
- directlabels * suggests
- ggplot2 * suggests
- knitr * suggests
- reshape2 * suggests
- rmarkdown * suggests
- testthat >= 3.0.0 suggests