Package: powerprior 1.0.0

powerprior: Conjugate Power Priors for Bayesian Analysis of Normal Data

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).

Authors:Yusuke Yamaguchi [aut, cre], Yifei Huang [aut]