dev_gamma_pois_zi

Zero-Inflated Gamma-Poisson Deviances

Functions to 'numericise' 'R' objects (coerce to numeric
objects), summarise 'MCMC' (Monte Carlo Markov Chain) samples and
calculate deviance residuals as well as 'R' translations of some
'BUGS' (Bayesian Using Gibbs Sampling), 'JAGS' (Just Another Gibbs
Sampler), 'STAN' and 'TMB' (Template Model Builder) functions.

Joe Thorley

extras

Helper Functions for Bayesian Analyses

Kirill Müller

Nadine Hussein

Poisson Consulting 

dev_gamma_pois_zi function

<dl><dt>x</dt>
<dd>A non-negative whole numeric vector of values.</dd>
<dt>lambda</dt>
<dd>A non-negative numeric vector of means.</dd>
<dt>theta</dt>
<dd>A non-negative numeric vector of the dispersion parameters for the gamma mixing distribution. The variance for the resultant gamma-Poisson distribution is lambda + lambda^2 * theta.</dd>
<dt>prob</dt>
<dd>A numeric vector of values between 0 and 1 of the probability of success.</dd>
<dt>res</dt>
<dd>A flag specifying whether to return the deviance residual as opposed to the deviance.</dd></dl>

Arguments

Zero-Inflated Gamma-Poisson Deviances — dev_gamma_pois_zi

<dl>

<dt>x</dt>
<dd>A non-negative whole numeric vector of values.</dd>


<dt>lambda</dt>
<dd>A non-negative numeric vector of means.</dd>


<dt>theta</dt>
<dd>A non-negative numeric vector of the dispersion parameters for the gamma mixing distribution. The variance for the resultant gamma-Poisson distribution is lambda + lambda^2 * theta.</dd>


<dt>prob</dt>
<dd>A numeric vector of values between 0 and 1 of the probability of success.</dd>


<dt>res</dt>
<dd>A flag specifying whether to return the deviance residual as opposed to the deviance.</dd>

</dl>

dev_gamma_pois_zi: Zero-Inflated Gamma-Poisson Deviances

Description

Usage

Value

Arguments

Examples