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RcausalEGM (version 0.3.3)

A General Causal Inference Framework by Encoding Generative Modeling

Description

CausalEGM is a general causal inference framework for estimating causal effects by encoding generative modeling, which can be applied in both discrete and continuous treatment settings. A description of the methods is given in Liu (2022) .

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install.packages('RcausalEGM')

Monthly Downloads

175

Version

0.3.3

License

MIT + file LICENSE

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Maintainer

Qiao Liu

Last Published

March 28th, 2023

Functions in RcausalEGM (0.3.3)

get_est

Make predictions with causalEGM model.
causalegm

Main function for estimating causal effect in either binary or continuous treatment settings.
install_causalegm

Install the python CausalEGM package