gnlsObject: Fitted gnls Object
Description
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. - apVaran 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. - calla list containing an image of the
gnls call that
produced the object. - coefficientsa vector with the estimated nonlinear model
coefficients.
- contrastsa 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.
- dimsa 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. - fitteda vector with the fitted values.
- modelStructan object inheriting from class
gnlsStruct,
representing a list of model components, such as corStruct and
varFunc objects. - groupsa vector with the correlation structure grouping factor,
if any is present.
- logLikthe log-likelihood at convergence.
- numIterthe number of iterations used in the iterative
algorithm.
- plist
- pmap
- residualsa vector with the residuals.
- sigmathe estimated residual standard error.
- varBetaan approximate covariance matrix of the
coefficients estimates.