hdm: High-Dimensional Metrics
Version 0.2.2

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.

Package details

AuthorMartin Spindler [cre, aut], Victor Chernozhukov [aut], Christian Hansen [aut]
Date of publication2017-04-05 14:01:27
MaintainerMartin Spindler <spindler@mea.mpisoc.mpg.de>
LicenseMIT + file LICENSE
Package repositoryView on R-Forge
Installation Install the latest version of this package by entering the following in R:
install.packages("hdm", repos="http://R-Forge.R-project.org")

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hdm documentation built on May 31, 2017, 4:39 a.m.