DoubleML

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.

Last 30 days

This package has been downloaded 1,033 times in the last 30 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 49 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 14,242 times in the last 365 days. That's enough downloads to make it mildly famous in niche technical communities. A badge of honor! The day with the most downloads was Oct 18, 2024 with 137 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.