gnlsObject               package:nlme               R Documentation

_F_i_t_t_e_d _g_n_l_s _O_b_j_e_c_t

_D_e_s_c_r_i_p_t_i_o_n:

     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'.

_V_a_l_u_e:

     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.

_A_u_t_h_o_r(_s):

     Jose Pinheiro and Douglas Bates

_S_e_e _A_l_s_o:

     `gnls', `gnlsStruct'

