CRAN/E | DoubleML

DoubleML

Double Machine Learning in R

Installation

About

Implementation of the double/debiased machine learning framework of Chernozhukov et al. (2018) doi:10.1111/ectj.12097 for partially linear regression models, partially linear instrumental variable regression models, interactive regression models and interactive instrumental variable regression models. 'DoubleML' allows estimation of the nuisance parts in these models by machine learning methods and computation of the Neyman orthogonal score functions. 'DoubleML' is built on top of 'mlr3' and the 'mlr3' ecosystem. The object-oriented implementation of 'DoubleML' based on the 'R6' package is very flexible. More information available in the publication in the Journal of Statistical Software: doi:10.18637/jss.v108.i03.

Citation DoubleML citation info
docs.doubleml.org/stable/index.html
github.com/DoubleML/doubleml-for-r/
Bug report File report

Key Metrics

Version 1.0.0
R ≥ 3.5.0
Published 2024-02-15 62 days ago
Needs compilation? no
License MIT
License File
CRAN checks DoubleML results

Downloads

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Maintainer

Maintainer

Philipp Bach

philipp.bach@uni-hamburg.de

Authors

Philipp Bach

aut / cre

Victor Chernozhukov

aut

Malte S. Kurz

aut

Martin Spindler

aut

Klaassen Sven

aut

Material

README
Reference manual
Package source

In Views

CausalInference
Econometrics
MachineLearning

Vignettes

DoubleML - An Object-Oriented Implementation of Double Machine Learning in R
Getting Started with DoubleML
Installing DoubleML

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

DoubleML archive

Depends

R ≥ 3.5.0

Imports

R6 ≥ 2.4.1
data.table ≥ 1.12.8
stats
checkmate
mlr3 ≥ 0.5.0
mlr3tuning ≥ 0.3.0
mvtnorm
utils
clusterGeneration
readstata13
mlr3learners ≥ 0.3.0
mlr3misc

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