hdm: High-Dimensional Metrics
Version 0.2.3

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) .

Package details

AuthorMartin Spindler [cre, aut], Victor Chernozhukov [aut], Christian Hansen [aut]
Date of publication2018-01-23 21:50:45 UTC
MaintainerMartin Spindler <[email protected]>
LicenseMIT + file LICENSE
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:

Try the hdm package in your browser

Any scripts or data that you put into this service are public.

hdm documentation built on Jan. 24, 2018, 1:02 a.m.