ddml: Double/Debiased Machine Learning (original) (raw)
Estimate common causal parameters using double/debiased machine learning as proposed by Chernozhukov et al. (2018) <doi:10.1111/ectj.12097>. 'ddml' simplifies estimation based on (short-)stacking as discussed in Ahrens et al. (2024) <doi:10.1177/1536867X241233641>, which leverages multiple base learners to increase robustness to the underlying data generating process.
| Version: | 0.3.0 |
|---|---|
| Depends: | R (≥ 3.6) |
| Imports: | methods, stats, AER, MASS, Matrix, nnls, quadprog, glmnet, ranger, xgboost |
| Suggests: | sandwich, covr, testthat (≥ 3.0.0), knitr, rmarkdown |
| Published: | 2024-10-02 |
| DOI: | 10.32614/CRAN.package.ddml |
| Author: | Achim Ahrens [aut], Christian B Hansen [aut], Mark E Schaffer [aut], Thomas Wiemann [aut, cre] |
| Maintainer: | Thomas Wiemann |
| BugReports: | https://github.com/thomaswiemann/ddml/issues |
| License: | GPL (≥ 3) |
| URL: | https://github.com/thomaswiemann/ddml,https://thomaswiemann.com/ddml/ |
| NeedsCompilation: | no |
| Materials: | README NEWS |
| CRAN checks: | ddml results |
Documentation:
Downloads:
Linking:
Please use the canonical formhttps://CRAN.R-project.org/package=ddmlto link to this page.