ebTobit
Empirical Bayesian Tobit Matrix Estimation
Estimation tools for multidimensional Gaussian means using empirical Bayesian g-modeling. Methods are able to handle fully observed data as well as left-, right-, and interval-censored observations (Tobit likelihood); descriptions of these methods can be found in Barbehenn and Zhao (2023) doi:10.48550/arXiv.2306.07239. Additional, lower-level functionality based on Kiefer and Wolfowitz (1956) doi:10.1214/aoms/1177728066 and Jiang and Zhang (2009) doi:10.1214/08-AOS638 is provided that can be used to accelerate many empirical Bayes and nonparametric maximum likelihood problems.
- Version1.0.2
- R versionunknown
- LicenseGPL-3
- Needs compilation?Yes
- Last release05/03/2024
Documentation
Team
Alton Barbehenn
MaintainerShow author detailsSihai Dave Zhao
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Insights
Last 30 days
This package has been downloaded 178 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 7 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 2,291 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 May 05, 2024 with 43 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
- Imports2 packages
- Suggests1 package
- Linking To3 packages