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hdm (version 0.1.0)

High-Dimensional Metrics

Description

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.

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Install

install.packages('hdm')

Monthly Downloads

1,651

Version

0.1.0

License

GPL-3

Maintainer

Last Published

February 2nd, 2016

Functions in hdm (0.1.0)