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✨
DESCRIPTION
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

10.17 score 163 stars 3 packages 515 scripts 2.6k downloads 18 exports 33 dependencies

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

TargetResultTimeFilesSyslog
linux-devel-x86_64OK311
source / vignettesOK306
linux-release-x86_64OK320
macos-release-arm64OK277
macos-oldrel-arm64OK272
windows-develOK286
windows-releaseOK293
windows-oldrelOK280
wasm-releaseOK134

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

Getting Started with DoubleML
Installation | Data | The causal model | The data-backend DoubleMLData | Learners to estimate the nuisance models | Cross-fitting, DML algorithms and Neyman-orthogonal score functions | Estimate double/debiased machine learning models
Rendered fromgetstarted.Rmdusingknitr::rmarkdown

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

DoubleML - An Object-Oriented Implementation of Double Machine Learning in R
Introduction | Long Package Vignette | References:
Rendered fromIntroduction_to_DoubleML.Rmdusingknitr::rmarkdown

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

Installing DoubleML
Installation | Installation from CRAN | Installation from GitHub
Rendered frominstall.Rmdusingknitr::rmarkdown

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