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\name{glpModel-class}
\title{Class "glpModel" of General Linear Prediction Models}
\Rdversion{1.1}
\docType{class}
\alias{glpModel-class}
\alias{coef,glpModel-method}
\alias{fitted,glpModel-method}
\alias{residuals,glpModel-method}
\description{
The class \code{"glpModel"} conceptually contains a very large class
of \emph{\dQuote{General Linear Prediction Models}}.
Its \code{resp} slot (of class \code{"\linkS4class{respModule}"}) may
model linear, non-linear, generalized linear and non-linear
generalized response models.
}
\section{Objects from the Class}{
Objects can be created by calls of the form \code{new("glpModel", ...)},
but typically rather are returned by our modeling functions, e.g., \code{glm4()}.
}
\section{Slots}{
\describe{
\item{\code{resp}:}{a \code{"\linkS4class{respModule}"} object.}
\item{\code{pred}:}{a \code{"\linkS4class{predModule}"} object.}
}
}
\section{Extends}{
Class \code{"\linkS4class{Model}"}, directly.%%-- FIXME move that stats4
}
\section{Methods}{
\describe{
\item{coef}{\code{signature(object = "glpModel")}: extract the
coefficient vector \eqn{\beta} from the object.}
\item{fitted}{\code{signature(object = "glpModel")}: fitted values;
there may be several types, corresponding to the residuals, see there
(below).}
\item{residuals}{\code{signature(object = "glpModel")}: residuals,
depending on the type of the model, there are several types of
residuals and correspondingly residuals,
see \code{\link[stats:glm.summaries]{residuals.glm}} from the
\pkg{stats} package.}
}
}
%\author{Douglas Bates}
\seealso{
\code{\link{glm4}()} returns fitted \code{glpModel} objects.
The constituents of this class are
\code{\linkS4class{respModule}} and
\code{\linkS4class{predModule}}, both of which have several sub
classes.
}
\examples{
showClass("glpModel")
## Use example(glm4) or see help(glm4) for many more examples.
}
\keyword{classes}
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