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.
- Version0.1.5
- R versionunknown
- LicenseGPL-3
- Needs compilation?No
- Last release05/01/2023
Team
Wei-Hsin Hsu
Li-Pang Chen
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Insights
Last 30 days
This package has been downloaded 213 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 6 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 2,549 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Jul 21, 2024 with 69 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
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Dependencies
- Depends1 package
- Imports2 packages