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GUD: Bayesian Modal Regression Based on the GUD Family

Provides probability density functions and sampling algorithms for three key distributions from the General Unimodal Distribution (GUD) family: the Flexible Gumbel (FG) distribution, the Double Two-Piece (DTP) Student-t distribution, and the Two-Piece Scale (TPSC) Student-t distribution. Additionally, this package includes a function for Bayesian linear modal regression, leveraging these three distributions for model fitting. The details of the Bayesian modal regression model based on the GUD family can be found at Liu, Huang, and Bai (2024) <doi:10.1016/j.csda.2024.108012>.

Version: 1.0.2
Depends: R (≥ 3.4.0)
Imports: methods, Rcpp (≥ 1.0.12), RcppParallel (≥ 5.0.1), rstan (≥ 2.32.6), rstantools (≥ 2.4.0), posterior (≥ 1.5.0), Rdpack (≥ 2.6)
LinkingTo: BH (≥ 1.66.0), Rcpp (≥ 1.0.12), RcppEigen (≥ 0.3.3.3.0), RcppParallel (≥ 5.0.1), rstan (≥ 2.32.6), StanHeaders (≥ 2.32.0)
Suggests: MASS, lattice, bayesplot (≥ 1.11.1), loo (≥ 2.7.0), knitr, rmarkdown
Published: 2024-07-01
DOI: 10.32614/CRAN.package.GUD
Author: Qingyang Liu ORCID iD [aut, cre], Xianzheng Huang ORCID iD [aut], Ray Bai ORCID iD [aut]
Maintainer: Qingyang Liu <qingyang at email.sc.edu>
License: GPL (≥ 3)
URL: https://github.com/rh8liuqy/Bayesian_modal_regression
NeedsCompilation: yes
SystemRequirements: GNU make
Citation: GUD citation info
Materials: README NEWS
CRAN checks: GUD results

Documentation:

Reference manual: GUD.pdf
Vignettes: Bayesian Modal Regression Analysis of 2003 United States Crime Data

Downloads:

Package source: GUD_1.0.2.tar.gz
Windows binaries: r-devel: GUD_1.0.2.zip, r-release: GUD_1.0.2.zip, r-oldrel: GUD_1.0.2.zip
macOS binaries: r-release (arm64): GUD_1.0.2.tgz, r-oldrel (arm64): GUD_1.0.2.tgz, r-release (x86_64): GUD_1.0.2.tgz, r-oldrel (x86_64): GUD_1.0.2.tgz
Old sources: GUD archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=GUD to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.