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% File nlme/man/gnlsObject.Rd
% Part of the nlme package for R
% Distributed under GPL 2 or later: see nlme/LICENCE.note
\name{gnlsObject}
\title{Fitted gnls Object}
\alias{gnlsObject}
\description{
An object returned by the \code{gnls} function, inheriting from class
\code{"gnls"} and also from class \code{"gls"}, and representing a
generalized nonlinear least squares fitted model. Objects of this
class have methods for the generic functions \code{anova},
\code{coef}, \code{fitted}, \code{formula}, \code{getGroups},
\code{getResponse}, \code{intervals}, \code{logLik}, \code{plot},
\code{predict}, \code{print}, \code{residuals}, \code{summary}, and
\code{update}.
}
\value{
The following components must be included in a legitimate \code{"gnls"}
object.
\item{apVar}{an approximate covariance matrix for the
variance-covariance coefficients. If \code{apVar = FALSE} in the
control values used in the call to \code{gnls}, this
component is equal to \code{NULL}.}
\item{call}{a list containing an image of the \code{gnls} call that
produced the object.}
\item{coefficients}{a vector with the estimated nonlinear model
coefficients.}
\item{contrasts}{a list of the contrast matrices used to represent factors
in the model formula. This information is important for making
predictions from a new data frame in which not all levels of the
original factors are observed. If no factors are used in the model,
this component will be an empty list.}
\item{dims}{a list with basic dimensions used in the model fit,
including the components \code{N} - the number of observations used in
the fit and \code{p} - the number of coefficients in the nonlinear
model.}
\item{fitted}{a vector with the fitted values.}
\item{modelStruct}{an object inheriting from class \code{gnlsStruct},
representing a list of model components, such as \code{corStruct} and
\code{varFunc} objects.}
\item{groups}{a vector with the correlation structure grouping factor,
if any is present.}
\item{logLik}{the log-likelihood at convergence.}
\item{numIter}{the number of iterations used in the iterative
algorithm.}
\item{plist}{}
\item{pmap}{}
\item{residuals}{a vector with the residuals.}
\item{sigma}{the estimated residual standard error.}
\item{varBeta}{an approximate covariance matrix of the
coefficients estimates.}
}
\author{José Pinheiro and Douglas Bates \email{bates@stat.wisc.edu}}
\seealso{\code{\link{gnls}}, \code{gnlsStruct}}
\keyword{models}
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