getAIC

an object of class <code><a rd-options="=cold-class" href="/link/cold?package=cold&version=2.0-3&to=%3Dcold-class" data-mini-rdoc="=cold-class::cold">cold</a></code>.

object

Methods for function <code>getAIC</code> extracting the Akaike information criterion of the fitted model object from class <code><a rd-options="" href="/link/cold?package=cold&version=2.0-3" data-mini-rdoc="cold::cold">cold</a></code>.

function

Performs regression analysis for longitudinal count data,
allowing for serial dependence among observations from a given
individual and two dimensional random effects on the linear predictor.
Estimation is via maximization of the exact likelihood of a suitably
defined model. Missing values and unbalanced data are allowed.
Details can be found in the accompanying scientific papers:
Goncalves & Cabral (2021, Journal of Statistical Software,
<doi:10.18637/jss.v099.i03>) and Goncalves et al.
(2007, Computational Statistics & Data Analysis,
<doi:10.1016/j.csda.2007.03.002>).

M Helena Gonalves

cold

Count Longitudinal Data

getAIC function

an object of class <code><a rd-options='=cold-class' href='cold'>cold</a></code>.

Methods for function <code>getAIC</code> extracting the Akaike information criterion of the fitted model object from class <code><a rd-options='' href='cold'>cold</a></code>.

getAIC: Extract the Akaike Information Criterion

Description

Usage

Arguments

Value