%
% Copyright (C) 2004-2008 Friedrich Leisch and Bettina Gruen
% $Id: FLXdist-class.Rd 4616 2010-10-11 06:08:09Z gruen $
%
\name{FLXdist-class}
\docType{class}
\alias{FLXdist-class}
\alias{predict,FLXdist-method}
\alias{predict,FLXM-method}
\alias{predict,FLXMRglm-method}
\alias{predict,FLXMRmgcv-method}
\alias{parameters,FLXdist-method}
\alias{prior}
\alias{prior,FLXdist-method}
\title{Class "FLXdist"}
\description{
Objects of class \code{FLXdist} represent unfitted finite mixture
models.
}
\usage{
\S4method{parameters}{FLXdist}(object, component=NULL, model=NULL, which = c("model",
"concomitant"), simplify=TRUE, drop=TRUE)
\S4method{predict}{FLXdist}(object, newdata=list(), aggregate=FALSE, ...)
}
\arguments{
\item{object}{An object of class "FLXdist".}
\item{component}{Number of component(s), if \code{NULL} all components
are returned.}
\item{model}{Number of model(s), if \code{NULL} all models are
returned.}
\item{which}{Specifies if the parameters of the component specific model or the
concomitant variable model are returned.}
\item{simplify}{Logical, if \code{TRUE} the returned values are
simplified to a vector or matrix if possible.}
\item{drop}{Logical, if \code{TRUE} the function tries to simplify the
return object by omitting lists of length one.}
\item{newdata}{Dataframe containing new data.}
\item{aggregate}{Logical, if \code{TRUE} then the predicted values for
each model aggregated over the components are returned.}
\item{\dots}{Passed to the method of the model class.}
}
\section{Slots}{
\describe{
\item{model}{List of \code{FLXM} objects.}
\item{prior}{Numeric vector with prior probabilities of clusters.}
\item{components}{List describing the components using
\code{FLXcomponent} objects.}
\item{\code{concomitant}:}{Object of class \code{"FLXP"}.}
\item{formula}{Object of class \code{"formula"}.}
\item{call}{The function call used to create the object.}
\item{k}{Number of clusters.}
}
}
\section{Accessor Functions}{
The following functions should be used for accessing the corresponding
slots:
\describe{
\item{\code{parameters}:}{The parameters for each model and component,
return value depends on the model.}
\item{\code{prior}:}{Numeric vector of prior class probabilities/component weights}
}
}
\author{Friedrich Leisch and Bettina Gruen}
\seealso{\code{FLXdist}}
\keyword{classes}