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.

Nicole Hill

extras

Helper Functions for Bayesian Analyses

Joe Thorley

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 for the mixture
models (student, gamma-Poisson and beta-binomial).</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 for the mixture
models (student, gamma-Poisson and beta-binomial).</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