aic-class

Representation of the output of function <code>AIC</code>.

classes

Provides a set of functions to analyse
overdispersed counts or proportions. Most of the methods are
already available elsewhere but are scattered in different
packages. The proposed functions should be considered as
complements to more sophisticated methods such as generalized
estimating equations (GEE) or generalized linear mixed effect
models (GLMM).

Renaud Lancelot

Analysis of Overdispersed Data

aic-class function

<dl> <dt>istats</dt>
<dd>A data frame with 3 columns describing the models indicated by the row names:<dl>
 <dt>df</dt>
<dd>number of parameters in the model</dd>
,
 <dt>AIC</dt>
<dd>Akaike information criterion for the model (see <code>AIC</code>)</dd>
,
 <dt>AICc</dt>
<dd>small-sample corrected Akaike information criterion for the model (see <code>AIC</code>).</dd></dl></dd> 
</dl>

Slots

<dl> <dt>summary</dt>
<dd><code>signature(object = "aic")</code></dd> <dt>show</dt>
<dd><code>signature(object = "aic")</code></dd> 
</dl>

Methods

Representation of Objects of Formal Class "aic" — aic-class

<dl>

 <dt>istats</dt>
<dd>A data frame with 3 columns describing the models indicated by the row names:<dl>
 <dt>df</dt>
<dd>number of parameters in the model</dd>
,
 <dt>AIC</dt>
<dd>Akaike information criterion for the model (see <code>AIC</code>)</dd>
,
 <dt>AICc</dt>
<dd>small-sample corrected Akaike information criterion for the model (see <code>AIC</code>).</dd>

 
</dl></dd>

 
</dl>

<dl>

 <dt>summary</dt>
<dd><code>signature(object = "aic")</code></dd>

 <dt>show</dt>
<dd><code>signature(object = "aic")</code></dd>

 
</dl>

aic-class: Representation of Objects of Formal Class "aic"

Description

Arguments

Slots

Methods