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powerprior  

Conjugate Power Priors for Bayesian Analysis of Normal Data
View on CRAN: Click here


Download and install powerprior package within the R console
Install from CRAN:
install.packages("powerprior")

Install from Github:
library("remotes")
install_github("cran/powerprior")

Install by package version:
library("remotes")
install_version("powerprior", "1.0.0")



Attach the package and use:
library("powerprior")
Maintained by
Yusuke Yamaguchi
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-11-11
Latest Update: 2025-11-11
Description:
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).
How to cite:
Yusuke Yamaguchi (2025). powerprior: Conjugate Power Priors for Bayesian Analysis of Normal Data. R package version 1.0.0, https://cran.r-project.org/web/packages/powerprior. Accessed 26 Jun. 2026.
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