MSIMST
Bayesian Monotonic Single-Index Regression Model with the Skew-T Likelihood
Incorporates a Bayesian monotonic single-index mixed-effect model with a multivariate skew-t likelihood, specifically designed to handle survey weights adjustments. Features include a simulation program and an associated Gibbs sampler for model estimation. The single-index function is constrained to be monotonic increasing, utilizing a customized Gaussian process prior for precise estimation. The model assumes random effects follow a canonical skew-t distribution, while residuals are represented by a multivariate Student-t distribution. Offers robust Bayesian adjustments to integrate survey weight information effectively.
- Version1.1
- R version≥ 3.4.0
- LicenseGPL (≥ 3)
- Needs compilation?Yes
- Last release09/16/2024
Documentation
Team
Qingyang Liu
Dipankar Bandyopadhyay
Show author detailsRolesAuthorDebdeep Pati
Show author detailsRolesAuthor
Insights
Last 30 days
This package has been downloaded 141 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 9 times.
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Last 365 days
This package has been downloaded 1,006 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 Sep 20, 2024 with 27 downloads.
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Dependencies
- Imports6 packages
- Suggests4 packages
- Linking To2 packages