Implements conjugate power priors for efficient Bayesian analysis of normal data. Power priors allow principled incorporation of historical information while controlling the degree of borrowing through a discounting parameter (Ibrahim and Chen (2000) <doi:10.1214/ss/1009212519>). This package provides closed-form conjugate representations for both univariate and multivariate normal data using Normal-Inverse-Chi-squared and Normal-Inverse-Wishart distributions, eliminating the need for MCMC sampling. The conjugate framework builds upon standard Bayesian methods described in Gelman et al. (2013, ISBN:978-1439840955).
| Version: | 1.0.0 |
| Imports: | stats, MASS, LaplacesDemon, ggplot2, shiny, shinydashboard, shinyjs, DT, dplyr, tidyr, rlang |
| Suggests: | testthat (≥ 3.0.0), rmarkdown |
| Published: | 2025-11-11 |
| DOI: | 10.32614/CRAN.package.powerprior |
| Author: | Yusuke Yamaguchi [aut, cre], Yifei Huang [aut] |
| Maintainer: | Yusuke Yamaguchi <yamagubed at gmail.com> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | no |
| Materials: | README, NEWS |
| CRAN checks: | powerprior results |
| Reference manual: | powerprior.html , powerprior.pdf |
| Package source: | powerprior_1.0.0.tar.gz |
| Windows binaries: | r-devel: powerprior_1.0.0.zip, r-release: powerprior_1.0.0.zip, r-oldrel: powerprior_1.0.0.zip |
| macOS binaries: | r-release (arm64): powerprior_1.0.0.tgz, r-oldrel (arm64): powerprior_1.0.0.tgz, r-release (x86_64): powerprior_1.0.0.tgz, r-oldrel (x86_64): powerprior_1.0.0.tgz |
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