coda_wrapper

Utility function to call MCMC diagnostic functions in the coda package

Bayesian Beta Regression, adapted for bounded discrete responses, commonly seen in survey responses.
Estimation is done via Markov Chain Monte Carlo sampling, using a Gibbs wrapper around univariate slice sampler
(Neal (2003) <DOI:10.1214/aos/1056562461>), as implemented in the R package MfUSampler
(Mahani and Sharabiani (2017) <DOI: 10.18637/jss.v078.c01>).

Alireza Mahani

Discrete Beta Regression

Mansour Sharabiani

Alex Bottle

Cathy Price

coda_wrapper function

<dl> <dt>dbr_obj</dt>
<dd>An object of class <code>dbr</code>, typically the output of the function <code>dbr</code>.</dd> <dt>coda_function</dt>
<dd>A function in the coda package, with first argument being an <code>mcmc</code> object.</dd> <dt>...</dt>
<dd>Arguments to be passed to <code>coda_function</code>.</dd></dl>

Arguments

Mansour T.A. Sharabiani, Alireza S. Mahani

Author

Utility function to call MCMC diagnostic functions in the coda package — coda_wrapper

<dl>

 <dt>dbr_obj</dt>
<dd>An object of class <code>dbr</code>, typically the output of the function <code>dbr</code>.</dd>

 <dt>coda_function</dt>
<dd>A function in the coda package, with first argument being an <code>mcmc</code> object.</dd>

 <dt>...</dt>
<dd>Arguments to be passed to <code>coda_function</code>.</dd>

</dl>

coda_wrapper: Utility function to call MCMC diagnostic functions in the coda package

Description

Usage

Value

Arguments

Author

Examples