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) doi:10.48550/arXiv.2212.05925.
- Version0.3.3
- R versionunknown
- LicenseMIT
- LicenseLICENSE
- Needs compilation?No
- Last release03/28/2023
Documentation
Team
Qiao Liu
Balasubramanian Narasimhan
Show author detailsRolesContributorWing Wong
Show author detailsRolesAuthor
Insights
Last 30 days
Last 365 days
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports1 package
- Suggests3 packages