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.
|Edward H. Kennedy
|Edward H. Kennedy <firstname.lastname@example.org>
|View on GitHub
Install the latest version of this package by entering the following in R:
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.