dtruncated_nbinom2

dtruncated_poisson

dtruncated_nbinom1

Probability functions for k-truncated Poisson and negative binomial distributions.

Fit linear and generalized linear mixed models with various
extensions, including zero-inflation. The models are fitted using maximum
likelihood estimation via 'TMB' (Template Model Builder). Random effects are
assumed to be Gaussian on the scale of the linear predictor and are integrated
out using the Laplace approximation. Gradients are calculated using automatic
differentiation.

Mollie Brooks

glmmTMB

Generalized Linear Mixed Models using Template Model Builder

Ben Bolker

Kasper Kristensen

Martin Maechler

Arni Magnusson

Maeve McGillycuddy

Hans Skaug

Anders Nielsen

Casper Berg

Koen van Bentham

Nafis Sadat

Daniel Lüdecke

Russ Lenth

Joseph O'Brien

Charles J. Geyer

Mikael Jagan

Brenton Wiernik

Daniel B. Stouffer

dtruncated_nbinom2 function

<dl><dt>x</dt>
<dd>value</dd>
<dt>size</dt>
<dd>number of trials/overdispersion parameter</dd>
<dt>mu</dt>
<dd>mean parameter</dd>
<dt>k</dt>
<dd>truncation parameter</dd>
<dt>log</dt>
<dd>(logical) return log-probability?</dd>
<dt>lambda</dt>
<dd>mean parameter</dd>
<dt>phi</dt>
<dd>overdispersion parameter</dd></dl>

Arguments

truncated distributions — dtruncated_nbinom2

<dl>

<dt>x</dt>
<dd>value</dd>


<dt>size</dt>
<dd>number of trials/overdispersion parameter</dd>


<dt>mu</dt>
<dd>mean parameter</dd>


<dt>k</dt>
<dd>truncation parameter</dd>


<dt>log</dt>
<dd>(logical) return log-probability?</dd>


<dt>lambda</dt>
<dd>mean parameter</dd>


<dt>phi</dt>
<dd>overdispersion parameter</dd>

</dl>

truncated distributions

dtruncated_nbinom2: truncated distributions

Description

Usage

Arguments