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 objectoriented 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>.
Package details 


Author  Philipp Bach [aut, cre], Victor Chernozhukov [aut], Malte S. Kurz [aut], Martin Spindler [aut], Klaassen Sven [aut] 
Maintainer  Philipp Bach <philipp.bach@unihamburg.de> 
License  MIT + file LICENSE 
Version  1.0.1 
URL  https://docs.doubleml.org/stable/index.html https://github.com/DoubleML/doublemlforr/ 
Package repository  View on CRAN 
Installation 
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