gnlsObject               package:nlme               R Documentation

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.  

   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.

   plist: 

    pmap: 

residuals: a vector with the residuals.

   sigma: the estimated residual standard error.

 varBeta: an approximate covariance matrix of the coefficients
          estimates.

Author(s):

     Jose Pinheiro Jose.Pinheiro@pharma.novartis.com and Douglas Bates
     bates@stat.wisc.edu

See Also:

     'gnls', 'gnlsStruct'

