IVDML: Double Machine Learning with Instrumental Variables andHeterogeneity
Instrumental variable (IV) estimators for homogeneous and heterogeneous treatment effects with efficient machine learning instruments. The estimators are based on double/debiased machine learning allowing for nonlinear and potentially high-dimensional control variables. Details can be found in Scheidegger, Guo and Bühlmann (2025) "Inference for heterogeneous treatment effects with efficient instruments and machine learning" <doi:10.48550/arXiv.2503.03530>.
| Version: | 1.0.1 |
| Imports: | mgcv,ranger, stats,xgboost (≥ 3.1.2.1) |
| Suggests: | testthat (≥ 3.0.0) |
| Published: | 2025-12-12 |
| DOI: | 10.32614/CRAN.package.IVDML |
| Author: | Cyrill Scheidegger [aut, cre, cph] |
| Maintainer: | Cyrill Scheidegger <cyrill.scheidegger at stat.math.ethz.ch> |
| License: | GPL (≥ 3) |
| URL: | https://github.com/cyrillsch/IVDML |
| NeedsCompilation: | no |
| Materials: | README,NEWS |
| CRAN checks: | IVDML results |
Documentation:
| Reference manual: | IVDML.html ,IVDML.pdf |
Downloads:
| Package source: | IVDML_1.0.1.tar.gz |
| Windows binaries: | r-devel:IVDML_1.0.1.zip, r-release:IVDML_1.0.1.zip, r-oldrel:IVDML_1.0.1.zip |
| macOS binaries: | r-release (arm64):IVDML_1.0.1.tgz, r-oldrel (arm64):IVDML_1.0.1.tgz, r-release (x86_64):IVDML_1.0.1.tgz, r-oldrel (x86_64):IVDML_1.0.1.tgz |
| Old sources: | IVDML archive |
Linking:
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