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.

Package details

AuthorPhilipp Bach [aut], Victor Chernozhukov [aut], Malte S. Kurz [aut, cre], Martin Spindler [aut]
MaintainerMalte S. Kurz <>
LicenseMIT + file LICENSE
Package repositoryView on CRAN
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DoubleML documentation built on Oct. 14, 2021, 9:06 a.m.