.\" -*- nroff -*- generated from .Rd format
.BG
.FN gnlsObject
.TL
Fitted gnls Object
.DN
An object returned by the `gnls' function, inheriting from class
`gnls' and also from class `gls', and representing a
generalized nonlinear least squares fitted model. Objects of this
class have methods for the generic functions  `anova',
`coef', `fitted', `formula', `getGroups',
`getResponse', `intervals', `logLik', `plot',
`predict', `print', `residuals', `summary', and
`update'.
.RT
The following components must be included in a legitimate `gnls'
object. 
.AG apVar
an approximate covariance matrix for the
variance-covariance coefficients. If `apVar = FALSE' in the list
of control values used in the call to `gnls', this
component is equal to `NULL'.
.AG call
a list containing an image of the `gnls' call that
produced the object.
.AG coefficients
a vector with the estimated nonlinear model
coefficients.
.AG contrasts
a list with the contrasts 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.
.AG dims
a list with basic dimensions used in the model fit,
including the components `N' - the number of observations used in
the fit and `p' - the number of coefficients in the nonlinear
model.
.AG fitted
a vector with the fitted values.
.AG modelStruct
an object inheriting from class `gnlsStruct',
representing a list of model components, such as `corStruct' and
`varFunc' objects.
.AG groups
a vector with the correlation structure grouping factor,
if any is present.
.AG logLik
the log-likelihood at convergence.
.AG numIter
the number of iterations used in the iterative
algorithm.
.AG residuals
a vector with the residuals.
.AG sigma
the estimated residual standard error.
.AG varBeta
an approximate covariance matrix of the
coefficients estimates.

.SA
`gnls', `gnlsStruct'
.KW models
.WR
