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RcausalEGM

A General Causal Inference Framework by Encoding Generative Modeling

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) <arXiv:2212.05925>.

Versions across snapshots

VersionRepositoryFileSize
0.3.3 rolling linux/jammy R-4.5 RcausalEGM_0.3.3.tar.gz 186.4 KiB
0.3.3 rolling linux/noble R-4.5 RcausalEGM_0.3.3.tar.gz 186.3 KiB
0.3.3 rolling source/ R- RcausalEGM_0.3.3.tar.gz 170.3 KiB
0.3.3 latest linux/jammy R-4.5 RcausalEGM_0.3.3.tar.gz 186.4 KiB
0.3.3 latest linux/noble R-4.5 RcausalEGM_0.3.3.tar.gz 186.3 KiB
0.3.3 latest source/ R- RcausalEGM_0.3.3.tar.gz 170.3 KiB
0.3.3 2026-04-26 source/ R- RcausalEGM_0.3.3.tar.gz 170.3 KiB
0.3.3 2026-04-23 source/ R- RcausalEGM_0.3.3.tar.gz 170.3 KiB
0.3.3 2026-04-09 windows/windows R-4.5 RcausalEGM_0.3.3.zip 190.2 KiB
0.3.3 2025-04-20 source/ R- RcausalEGM_0.3.3.tar.gz 170.3 KiB

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