Package: RcausalEGM 0.3.3

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>.

Authors:Qiao Liu [aut, cre], Wing Wong [aut], Balasubramanian Narasimhan [ctb]

RcausalEGM_0.3.3.tar.gz
RcausalEGM_0.3.3.zip(r-4.7-any)RcausalEGM_0.3.3.zip(r-4.6-any)RcausalEGM_0.3.3.zip(r-4.5-any)
RcausalEGM_0.3.3.tgz(r-4.6-any)RcausalEGM_0.3.3.tgz(r-4.5-any)
RcausalEGM_0.3.3.tar.gz(r-4.7-any)RcausalEGM_0.3.3.tar.gz(r-4.6-any)
RcausalEGM_0.3.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
RcausalEGM/json (API)

# Install 'RcausalEGM' in R:
install.packages('RcausalEGM', repos = c('https://teddy880.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/suwonglab/causalegm/issues

On CRAN:

Conda:

2.45 score 14 scripts 194 downloads 3 exports 12 dependencies

Last updated from:af91dbabbd. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK132
source / vignettesOK236
linux-releaseOK127
macos-releaseOK190
macos-oldrelOK179
windows-develOK135
windows-releaseOK125
windows-oldrelOK136
wasm-releaseOK95

Exports:causalegmget_estinstall_causalegm

Dependencies:herejsonlitelatticeMatrixpngrappdirsRcppRcppTOMLreticulaterlangrprojrootwithr

Binary Treatment
Data Generation | Model training | Treatment Effect Estimation | Predicting Counterfactual Outcome | Estimating Conditional Average Treatment Effect (CATE)
Rendered frombinary_treatment.Rmdusingknitr::rmarkdown

Last update: 2023-03-28
Started: 2023-03-28

Continous Treatment
Data Generation | Model training | Treatment Effect Estimation | Plot of the average dose-response function (ADRF)
Rendered fromcontinous_treatment.Rmdusingknitr::rmarkdown

Last update: 2023-03-28
Started: 2023-03-28