log_cmp

Log density of the normalized component of the Conway-Maxwell-Poisson

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

log_cmp function

<dl><dt>y</dt>
<dd>Value</dd>
<dt>mu</dt>
<dd>Location parameter</dd>
<dt>nu</dt>
<dd>Shape parameter</dd></dl>

Arguments

Log density of the normalized component of the Conway-Maxwell-Poisson — log_cmp

<dl>

<dt>y</dt>
<dd>Value</dd>


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


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

</dl>

log_cmp: Log density of the normalized component of the Conway-Maxwell-Poisson

Description

Usage

Value

Arguments