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]

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Peer review:

On CRAN:

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

3 exports 0.00 score 13 dependencies 221 downloads

Last updated 1 years agofrom:7f2ceb2e3c. Checks:OK: 7. Indexed: yes.

Exports:CHEMIST_packageData_GenFATE

Dependencies:foreignGPArotationLaplacesDemonlatticeMASSmnormtnlmepsychpsychToolsR.methodsS3R.oortfXICOR