IVDML
Double Machine Learning with Instrumental Variables and Heterogeneity
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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0.1 |
rolling linux/jammy R-4.5 | IVDML_1.0.1.tar.gz |
96.8 KiB |
1.0.1 |
rolling linux/noble R-4.5 | IVDML_1.0.1.tar.gz |
96.7 KiB |
1.0.1 |
rolling source/ R- | IVDML_1.0.1.tar.gz |
30.1 KiB |
1.0.1 |
latest linux/jammy R-4.5 | IVDML_1.0.1.tar.gz |
96.8 KiB |
1.0.1 |
latest linux/noble R-4.5 | IVDML_1.0.1.tar.gz |
96.7 KiB |
1.0.1 |
latest source/ R- | IVDML_1.0.1.tar.gz |
30.1 KiB |
1.0.1 |
2026-04-26 source/ R- | IVDML_1.0.1.tar.gz |
30.1 KiB |
1.0.1 |
2026-04-23 source/ R- | IVDML_1.0.1.tar.gz |
30.1 KiB |
1.0.1 |
2026-04-09 windows/windows R-4.5 | IVDML_1.0.1.zip |
99.3 KiB |
1.0.0 |
2025-04-20 source/ R- | IVDML_1.0.0.tar.gz |
29.8 KiB |