hdm
0.3.2High-Dimensional Metrics
Overview
Implementation of selected high-dimensional statistical and econometric methods for estimation and inference. Efficient estimators and uniformly valid confidence intervals for various low-dimensional causal/ structural parameters are provided which appear in high-dimensional approximately sparse models. Including functions for fitting heteroscedastic robust Lasso regressions with non-Gaussian errors and for instrumental variable (IV) and treatment effect estimation in a high-dimensional setting. Moreover, the methods enable valid post-selection inference and rely on a theoretically grounded, data-driven choice of the penalty. Chernozhukov, Hansen, Spindler (2016) arXiv:1603.01700.
Install
Health
- NOTE r-devel-linux-x86_64-debian-clang
- NOTE r-devel-linux-x86_64-debian-gcc
- NOTE2026-03-1012 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 67%
- Documented parameters
- 79%
- Return-value docs
- 92%
- References docs
- 47%
Downloads
Dependencies
Code & Tests
Datasets
People & History
5 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 0.3.2Latest
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- 0.3.12019-01-18 · diff ↗
- RR 3.5.0 released · 2018-04-23
- 0.2.32018-01-23 · diff ↗
- RR 3.4.0 released · 2017-04-21
- 0.2.02016-06-17 · diff ↗
- RR 3.3.0 released · 2016-05-03
- 0.1.02016-02-02
Show 1 earlier events
- RR 3.2.0 released · 2015-04-16
Package metadata
- First published
- 2016-02-02
- Total releases
- 5 / 10 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 3.0.0
- Bundled data
- 1.3 MB / 7 files
- Download size
- 1.5 MB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
Cite
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