hdm v0.3.1


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High-Dimensional Metrics

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>.

Functions in hdm

Name Description
LassoShooting.fit Shooting Lasso
coef.rlassoEffects Coefficients from S3 objects rlassoEffects
cps2012 cps2012 data set
print.rlasso Methods for S3 object rlasso
hdm-package hdm: High-Dimensional Metrics
lambdaCalculation Function for Calculation of the penalty parameter
predict.rlassologit Methods for S3 object rlassologit
rlassoATE Functions for estimation of treatment effects
print.rlassoIVselectZ Methods for S3 object rlassoIVselectZ
print.rlassoTE Methods for S3 object rlassoTE
rlassoIVselectZ Instrumental Variable Estimation with Lasso
print.rlassoIV Methods for S3 object rlassoIV
print.rlassoIVselectX Methods for S3 object rlassoIVselectX
Growth Data Growth data set
print.tsls Methods for S3 object tsls
p_adjust Multiple Testing Adjustment of p-values for S3 objects rlassoEffects and lm
pension Pension 401(k) data set
print_coef Printing coefficients from S3 objects rlassoEffects
print.rlassoEffects Methods for S3 object rlassoEffects
rlassologit rlassologit: Function for logistic Lasso estimation
rlasso rlasso: Function for Lasso estimation under homoscedastic and heteroscedastic non-Gaussian disturbances
rlassoEffects rigorous Lasso for Linear Models: Inference
rlassoIV Post-Selection and Post-Regularization Inference in Linear Models with Many Controls and Instruments
print.rlassologitEffects Methods for S3 object rlassologitEffects
rlassologitEffects rigorous Lasso for Logistic Models: Inference
tsls Two-Stage Least Squares Estimation (TSLS)
rlassoIVselectX Instrumental Variable Estimation with Selection on the exogenous Variables by Lasso
summary.rlassoEffects Summarizing rlassoEffects fits
AJR AJR data set
EminentDomain Eminent Domain data set
BLP BLP data set
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Last month downloads


Type Package
Date 2018-12-19
License MIT + file LICENSE
LazyData TRUE
VignetteBuilder knitr
RoxygenNote 6.1.0
Repository CRAN
Repository/R-Forge/Project hdm
Repository/R-Forge/Revision 160
Repository/R-Forge/DateTimeStamp 2019-01-18 15:08:29
Date/Publication 2019-01-18 21:50:17 UTC
NeedsCompilation no
Packaged 2019-01-18 15:34:25 UTC; rforge

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