Double Machine Learning in R
Generates data from a partially linear IV regression model with multiw...
Generates data from a partially linear regression model used in Cherno...
Generates data from a partially linear regression model used in a blog...
Generates data from a interactive regression (IRM) model.
Generates data from a partially linear IV regression model used in Che...
Wrapper for Double machine learning data-backend initialization from d...
Wrapper for Double machine learning data-backend initialization from m...
Abstract class DoubleML
Double machine learning data-backend for data with cluster variables
Double machine learning data-backend
Double machine learning for interactive IV regression models
Double machine learning for interactive regression models
Double machine learning for partially linear IV regression models
Double machine learning for partially linear regression models
Data set on financial wealth and 401(k) plan participation.
Data set on the Pennsylvania Reemployment Bonus experiment.
Generates data from a interactive IV regression (IIVM) model.
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>.
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