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
.
VALUE:
The following components must be included in a legitimate
gnls
object.
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.
call
a list containing an image of the
gnls call that
produced the object.
coefficients
a vector with the estimated nonlinear model
coefficients.
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.
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.
fitted
a vector with the fitted values.
modelStruct
an object inheriting from class
gnlsStruct,
representing a list of model components, such as
corStruct and
varFunc
objects.
groups
a vector with the correlation structure grouping factor,
if any is present.
logLik
the log-likelihood at convergence.
numIter
the number of iterations used in the iterative
algorithm.
residuals
a vector with the residuals.
sigma
the estimated residual standard error.
varBeta
an approximate covariance matrix of the
coefficients estimates.