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\name{Generics}
\alias{ICL}
\alias{KLdiv}
\alias{Lapply}
\alias{clusters}
\alias{getModel}
\alias{parameters}
\alias{posterior}
\alias{prior}
\alias{refit}
\alias{relabel}
\alias{ParseFormula}
\title{Generic Utility Functions}
\description{
A collection of standard generic functions for which other packages
provide methods.
}
\usage{
ICL(object, \dots)
KLdiv(object, \dots)
Lapply(object, FUN, \dots)
clusters(object, newdata, \dots)
getModel(object, \dots)
parameters(object, \dots)
posterior(object, newdata, \dots)
prior(object, \dots)
refit(object, newdata, \dots)
relabel(object, by, \dots)
ParseFormula(formula, data = list())
}
\arguments{
\item{object}{S4 classed object.}
\item{formula}{A model formula.}
\item{data}{An optional data frame.}
\item{FUN}{The function to be applied.}
\item{newdata}{Optional new data.}
\item{by}{Typically a character string specifying how to relabel the object.}
\item{\dots}{Some methods for these generic function may take
additional, optional arguments.}
}
\details{
\describe{
\item{ICL:}{Integrated Completed Likelihood criterion for model
selection.}
\item{KLdiv:}{Kullback-Leibler divergence.}
\item{Lapply:}{S4 generic for \code{lapply}}
\item{clusters:}{Get cluster membership information from a model or
compute it for new data.}
\item{getModel:}{Get single model from a collection of models.}
\item{parameters:}{Get parameters of a model (similar to but more
general than \code{\link{coefficients}}).}
\item{posterior:}{Get posterior probabilities from a model or
compute posteriors for new data.}
\item{prior:}{Get prior probabilities from a model.}
\item{refit:}{Refit a model (usually to obtain additional
information that was not computed or stored during the initial
fitting process).}
\item{relabel:}{Relabel a model (usually to obtain a new permutation
of labels in mixture models or cluster objects).}
}
}
\keyword{methods}
\author{Friedrich Leisch}
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