% % 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}