com_sampler

Sampler for the Conway-Maxwell-Poisson as described in Algorithm 2 - Benson &amp; Friel (2021)

Fits a Bayesian Regression Model for multivariate count data. This model assumes that the data is distributed according to the Conway-Maxwell-Poisson distribution, and for each response variable it is associate different covariates. This model allows to account for correlations between the counts by using latent effects based on the Chib and Winkelmann (2001) <http://www.jstor.org/stable/1392277> proposal.

Mauro Florez

MultRegCMP

Bayesian Multivariate Conway-Maxwell-Poisson Regression Model
for Correlated Count Data

com_sampler function

<dl><dt>mu</dt>
<dd>Location parameter</dd>
<dt>nu</dt>
<dd>Shape parameter</dd>
<dt>n</dt>
<dd>Number of draws (default = 1)</dd>
<dt>ndraws</dt>
<dd>Optional: Return the number of draws required to generate the n samples.</dd></dl>

Arguments

Rejection Sampler - COM-Poisson — com_sampler

<dl>

<dt>mu</dt>
<dd>Location parameter</dd>


<dt>nu</dt>
<dd>Shape parameter</dd>


<dt>n</dt>
<dd>Number of draws (default = 1)</dd>


<dt>ndraws</dt>
<dd>Optional: Return the number of draws required to generate the n samples.</dd>

</dl>

com_sampler: Rejection Sampler - COM-Poisson

Description

Usage

Value

Arguments

Examples