This package provides a variety of tools for nonparametric estimation of causal effects across a wide range of settings. The methods are based on the theory of influence functions, and can incorporate flexible machine learning and high-dimensional regression tools, while still yielding inference in the form of confidence intervals and hypothesis tests. Many of the methods are doubly robust.
|Author||Edward H. Kennedy|
|Maintainer||Edward H. Kennedy <email@example.com>|
|Package repository||View on GitHub|
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