Package: DoubleML 1.0.1.9000

Philipp Bach

DoubleML: Double Machine Learning in R

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>.

Authors:Philipp Bach [aut, cre], Victor Chernozhukov [aut], Malte S. Kurz [aut], Martin Spindler [aut], Klaassen Sven [aut]

DoubleML_1.0.1.9000.tar.gz
DoubleML_1.0.1.9000.zip(r-4.7)DoubleML_1.0.1.9000.zip(r-4.6)DoubleML_1.0.1.9000.zip(r-4.5)
DoubleML_1.0.1.9000.tgz(r-4.6-any)DoubleML_1.0.1.9000.tgz(r-4.5-any)
DoubleML_1.0.1.9000.tar.gz(r-4.7-any)DoubleML_1.0.1.9000.tar.gz(r-4.6-any)
DoubleML_1.0.1.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
DoubleML/json (API)

# Install 'DoubleML' in R:
install.packages('DoubleML', repos = c('https://doubleml.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/doubleml/doubleml-for-r/issues

On CRAN:

Conda:

causal-inferencedata-sciencedouble-machine-learningeconometricsmachine-learningmlr3statistics

10.19 score 162 stars 3 packages 626 scripts 2.3k downloads 18 exports 33 dependencies

Last updated from:e8227c8ac9. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK337
source / vignettesOK278
linux-release-x86_64OK297
macos-release-arm64OK302
macos-oldrel-arm64OK232
windows-develOK253
windows-releaseOK236
windows-oldrelOK243
wasm-releaseOK131

Exports:double_ml_data_from_data_framedouble_ml_data_from_matrixDoubleMLClusterDataDoubleMLDataDoubleMLIIVMDoubleMLIRMDoubleMLPLIVDoubleMLPLRDoubleMLSSMfetch_401kfetch_bonusmake_iivm_datamake_irm_datamake_pliv_CHS2015make_pliv_multiway_cluster_CKMS2021make_plr_CCDDHNR2018make_plr_turrell2018make_ssm_data

Dependencies:backportsbbotkcheckmatecliclusterGenerationcodetoolsdata.tabledigestevaluatefuturefuture.applyglobalslgrlistenvMASSmiraimlbenchmlr3mlr3learnersmlr3measuresmlr3miscmlr3tuningmvtnormnanonextpalmerpenguinsparadoxparallellyPRROCR6Rcppreadstata13rlanguuid

DoubleML - An Object-Oriented Implementation of Double Machine Learning in R

Rendered fromIntroduction_to_DoubleML.Rmdusingknitr::rmarkdownon May 11 2026.

Last update: 2024-02-15
Started: 2021-06-03

Getting Started with DoubleML

Rendered fromgetstarted.Rmdusingknitr::rmarkdownon May 11 2026.

Last update: 2025-04-10
Started: 2021-06-03

Installing DoubleML

Rendered frominstall.Rmdusingknitr::rmarkdownon May 11 2026.

Last update: 2021-01-25
Started: 2020-11-13

Readme and manuals

Help Manual

Help pageTopics
Wrapper for Double machine learning data-backend initialization from data.frame.double_ml_data_from_data_frame
Wrapper for Double machine learning data-backend initialization from matrix.double_ml_data_from_matrix
Abstract class DoubleMLDoubleML
Double machine learning data-backend for data with cluster variablesDoubleMLClusterData
Double machine learning data-backendDoubleMLData
Double machine learning for interactive IV regression modelsDoubleMLIIVM
Double machine learning for interactive regression modelsDoubleMLIRM
Double machine learning for partially linear IV regression modelsDoubleMLPLIV
Double machine learning for partially linear regression modelsDoubleMLPLR
Double machine learning for sample selection modelsDoubleMLSSM
Data set on financial wealth and 401(k) plan participation.fetch_401k
Data set on the Pennsylvania Reemployment Bonus experiment.fetch_bonus
Generates data from a interactive IV regression (IIVM) model.make_iivm_data
Generates data from a interactive regression (IRM) model.make_irm_data
Generates data from a partially linear IV regression model used in Chernozhukov, Hansen and Spindler (2015).make_pliv_CHS2015
Generates data from a partially linear IV regression model with multiway cluster sample used in Chiang et al. (2021).make_pliv_multiway_cluster_CKMS2021
Generates data from a partially linear regression model used in Chernozhukov et al. (2018)make_plr_CCDDHNR2018
Generates data from a partially linear regression model used in a blog article by Turrell (2018).make_plr_turrell2018
Generates data from a sample selection model (SSM).make_ssm_data