check_compatibility

Performs a simple compatibility check between historical and current data
to help guide the choice of discounting parameter.

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

powerprior

Conjugate Power Priors for Bayesian Analysis of Normal Data

Yifei Huang

check_compatibility function

<dl><dt>historical_data</dt>
<dd>Historical data</dd>
<dt>current_data</dt>
<dd>Current data</dd>
<dt>alpha</dt>
<dd>Significance level for compatibility test (default: 0.05)</dd></dl>

Arguments

Check Data Compatibility — check_compatibility

<dl>

<dt>historical_data</dt>
<dd>Historical data</dd>


<dt>current_data</dt>
<dd>Current data</dd>


<dt>alpha</dt>
<dd>Significance level for compatibility test (default: 0.05)</dd>

</dl>

check_compatibility: Check Data Compatibility

Description

Usage

Value

Arguments

Examples