Package: CHEMIST 0.1.5

CHEMIST: Causal Inference with High-Dimensional Error-Prone Covariates and Misclassified Treatments

We aim to deal with the average treatment effect (ATE), where the data are subject to high-dimensionality and measurement error. This package primarily contains two functions, which are used to generate artificial data and estimate ATE with high-dimensional and error-prone data accommodated.

Authors:Wei-Hsin Hsu [aut, cre], Li-Pang Chen [aut]

CHEMIST_0.1.5.tar.gz
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CHEMIST.pdf |CHEMIST.html✨
CHEMIST/json (API)

# Install 'CHEMIST' in R:
install.packages('CHEMIST', repos = c('https://anson60214.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 218 downloads 3 exports 13 dependencies

Last updated 2 years agofrom:7f2ceb2e3c. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 27 2025
R-4.5-winOKMar 27 2025
R-4.5-macOKMar 27 2025
R-4.5-linuxOKMar 27 2025
R-4.4-winOKMar 27 2025
R-4.4-macOKMar 27 2025
R-4.4-linuxOKMar 27 2025
R-4.3-winOKMar 27 2025
R-4.3-macOKMar 27 2025

Exports:CHEMIST_packageData_GenFATE

Dependencies:foreignGPArotationLaplacesDemonlatticeMASSmnormtnlmepsychpsychToolsR.methodsS3R.oortfXICOR