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ddml  

Double/Debiased Machine Learning
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("ddml", "0.3.0")



Attach the package and use:
library("ddml")
Maintained by
Thomas Wiemann
[Scholar Profile | Author Map]
First Published: 2023-08-29
Latest Update: 2024-01-09
Description:
Estimate common causal parameters using double/debiased machine learning as proposed by Chernozhukov et al. (2018) . 'ddml' simplifies estimation based on (short-)stacking as discussed in Ahrens et al. (2024) , which leverages multiple base learners to increase robustness to the underlying data generating process.
How to cite:
Thomas Wiemann (2023). ddml: Double/Debiased Machine Learning. R package version 0.3.0, https://cran.r-project.org/web/packages/ddml. Accessed 29 Mar. 2025.
Previous versions and publish date:
0.1.0 (2023-08-29 18:40), 0.2.0 (2024-01-09 09:20), 0.2.1 (2024-05-26 10:00), 0.2.2 (2024-06-27 02:10)
Other packages that cited ddml R package
View ddml citation profile
Other R packages that ddml depends, imports, suggests or enhances
Complete documentation for ddml
Functions, R codes and Examples using the ddml R package
Some associated functions: AE98 . crosspred . crossval . ddml . ddml_ate . ddml_fpliv . ddml_late . ddml_pliv . ddml_plm . mdl_glm . mdl_glmnet . mdl_ranger . mdl_xgboost . ols . shortstacking . summary.ddml_ate . summary.ddml_plm . 
Some associated R codes: AE98.R . crosspred.R . crossval.R . ddml.R . ddml_ate.R . ddml_att.R . ddml_fpliv.R . ddml_late.R . ddml_pliv.R . ddml_plm.R . ensemble.R . get_CEF.R . help_functions.R . ml_wrappers.R . ols.R . shortstacking.R .  Full ddml package functions and examples
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