# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "powerprior" in publications use:'
type: software
license: MIT
title: 'powerprior: Conjugate Power Priors for Bayesian Analysis of Normal Data'
version: 1.0.0
doi: 10.32614/CRAN.package.powerprior
abstract: 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) <https://doi.org/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).
authors:
- family-names: Yamaguchi
  given-names: Yusuke
  email: yamagubed@gmail.com
- family-names: Huang
  given-names: Yifei
repository: https://cran.r-universe.dev
commit: bc51aa1f29441fa034744affbc755e7bb167e047
date-released: '2025-11-11'
contact:
- family-names: Yamaguchi
  given-names: Yusuke
  email: yamagubed@gmail.com