CRAN/E | hdm

hdm

High-Dimensional Metrics

Installation

About

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) .

Citation hdm citation info

Key Metrics

Version 0.3.2
R ≥ 3.0.0
Published 2024-02-14 44 days ago
Needs compilation? no
License MIT
License File
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Maintainer

Maintainer

Martin Spindler

martin.spindler@gmx.de

Authors

Martin Spindler

cre / aut

Victor Chernozhukov

aut

Christian Hansen

aut

Philipp Bach

ctb

Material

README
Reference manual
Package source

In Views

CausalInference
Econometrics
MachineLearning

Vignettes

High-Dimensional Metrics in R

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

hdm archive

Depends

R ≥ 3.0.0

Imports

MASS
glmnet
ggplot2
checkmate
Formula
methods

Suggests

testthat
knitr
rmarkdown
formatR
xtable
mvtnorm
markdown

Reverse Depends

tsapp

Reverse Imports

causalweight
hdcate