powerprior

powerprior-package

Additional helper functions for power prior analysis

internal

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).

Yusuke Yamaguchi

Conjugate Power Priors for Bayesian Analysis of Normal Data

Yifei Huang

powerprior-package function

Maintainer: Yusuke Yamaguchi <a href="/link/yamagubed%40gmail.com?package=powerprior&version=1.0.0" data-mini-rdoc="powerprior::yamagubed@gmail.com">yamagubed@gmail.com</a>
Authors:<ul>
<li>Yifei Huang</li>
</ul>

Author

Utility Functions for powerprior Package — powerprior-package

Maintainer: Yusuke Yamaguchi <a href='mailto:yamagubed@gmail.com'>yamagubed@gmail.com</a>
Authors:<ul>
<li>Yifei Huang</li>
</ul>

powerprior-package: Utility Functions for powerprior Package

Description

Arguments

Author