Package: hdm
Type: Package
Title: High-Dimensional Metrics
Version: 0.3.2
Date: 2024-02-09
Authors@R: c(
  person("Martin", "Spindler", email="martin.spindler@gmx.de", role=c("cre", "aut")),
  person("Victor", "Chernozhukov", role="aut"),
  person("Christian", "Hansen", role="aut"),
  person("Philipp", "Bach", email = "philipp.bach@uni-hamburg.de", role="ctb"))
Depends: R (>= 3.0.0)
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.
    Chernozhukov, Hansen, Spindler (2016) <arXiv:1603.01700>.
License: MIT + file LICENSE
LazyData: TRUE
Imports: MASS, glmnet, ggplot2, checkmate, Formula, methods
Suggests: testthat, knitr, rmarkdown, formatR, xtable, mvtnorm,
        markdown
VignetteBuilder: knitr
Encoding: UTF-8
RoxygenNote: 7.3.1
NeedsCompilation: no
Packaged: 2024-02-14 15:17:25 UTC; bachp
Author: Martin Spindler [cre, aut],
  Victor Chernozhukov [aut],
  Christian Hansen [aut],
  Philipp Bach [ctb]
Maintainer: Martin Spindler <martin.spindler@gmx.de>
Repository: CRAN
Date/Publication: 2024-02-14 21:20:02 UTC
Built: R 4.5.0; ; 2025-04-03 10:01:56 UTC; unix
