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DoubleML  

Double Machine Learning in R
View on CRAN: Click here


Download and install DoubleML package within the R console
Install from CRAN:
install.packages("DoubleML")

Install from Github:
library("remotes")
install_github("cran/DoubleML")

Install by package version:
library("remotes")
install_version("DoubleML", "1.0.2")



Attach the package and use:
library("DoubleML")
Maintained by
Philipp Bach
[Scholar Profile | Author Map]
First Published: 2020-12-16
Latest Update: 2023-03-31
Description:
Implementation of the double/debiased machine learning framework of Chernozhukov et al. (2018) 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: .
How to cite:
Philipp Bach (2020). DoubleML: Double Machine Learning in R. R package version 1.0.2, https://cran.r-project.org/web/packages/DoubleML. Accessed 06 May. 2025.
Previous versions and publish date:
0.1.1 (2020-12-16 11:30), 0.1.2 (2021-01-25 12:20), 0.2.0 (2021-03-05 18:30), 0.2.1 (2021-03-14 17:50), 0.3.0 (2021-06-04 12:10), 0.3.1 (2021-08-02 16:30), 0.4.0 (2021-10-14 11:00), 0.4.1 (2021-10-26 16:00), 0.5.0 (2022-06-14 12:00), 0.5.1 (2022-08-19 13:50), 0.5.2 (2022-11-24 00:50), 0.5.3 (2023-03-31 12:30), 1.0.0 (2024-02-15 16:20), 1.0.1 (2024-06-05 18:40)
Other packages that cited DoubleML R package
View DoubleML citation profile
Other R packages that DoubleML depends, imports, suggests or enhances
Complete documentation for DoubleML
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