%0 Generic %1 chernozhukov2016highdimensional %A Chernozhukov, Victor %A Hansen, Chris %A Spindler, Martin %D 2016 %K multivariate rstats statistics %T High-Dimensional Metrics in R %U http://arxiv.org/abs/1603.01700 %X The package High-dimensional Metrics (\Rpackagehdm) is an evolving collection of statistical methods for estimation and quantification of uncertainty in high-dimensional approximately sparse models. It focuses on providing semi-parametrically efficient estimators, confidence intervals, and significance testing for low-dimensional subcomponents of the high-dimensional parameter vector. This vignette offers a brief introduction and a tutorial to the implemented methods. \R and the package \Rpackagehdm are open-source software projects and can be freely downloaded from CRAN: http://cran.r-project.org.

@misc{chernozhukov2016highdimensional, abstract = {The package High-dimensional Metrics (\Rpackage{hdm}) is an evolving collection of statistical methods for estimation and quantification of uncertainty in high-dimensional approximately sparse models. It focuses on providing semi-parametrically efficient estimators, confidence intervals, and significance testing for low-dimensional subcomponents of the high-dimensional parameter vector. This vignette offers a brief introduction and a tutorial to the implemented methods. \R and the package \Rpackage{hdm} are open-source software projects and can be freely downloaded from CRAN: \texttt{http://cran.r-project.org}.}, added-at = {2016-03-08T22:41:57.000+0100}, author = {Chernozhukov, Victor and Hansen, Chris and Spindler, Martin}, biburl = {https://www.bibsonomy.org/bibtex/23ccbb94e578d551284d46f3b4e960eaf/shabbychef}, description = {High-Dimensional Metrics in R}, interhash = {88f826aa5811ae5fb0ec6840ba611cd5}, intrahash = {3ccbb94e578d551284d46f3b4e960eaf}, keywords = {multivariate rstats statistics}, note = {cite arxiv:1603.01700Comment: 25 pages; vignette for the R package hdm}, timestamp = {2016-03-08T22:41:57.000+0100}, title = {High-Dimensional Metrics in R}, url = {http://arxiv.org/abs/1603.01700}, year = 2016 }