nlmeObject               package:nlme               R Documentation

_F_i_t_t_e_d _n_l_m_e _O_b_j_e_c_t

_D_e_s_c_r_i_p_t_i_o_n:

     An object returned by the 'nlme' function, inheriting from class
     'nlme', also inheriting from class 'lme', and representing a
     fitted nonlinear mixed-effects model. Objects of this class have
     methods for the generic functions  'anova', 'coef', 'fitted',
     'fixed.effects', 'formula', 'getGroups', 'getResponse',
     'intervals', 'logLik', 'pairs', 'plot', 'predict', 'print',
     'random.effects', 'residuals', 'summary', and 'update'.

_V_a_l_u_e:

     The following components must be included in a legitimate 'nlme'
     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 'nlme', this component is equal to
          'NULL'.

    call: a list containing an image of the 'nlme' call that produced
          the object.

coefficients: a list with two components, 'fixed' and 'random', where
          the first is a vector containing the estimated fixed effects
          and the second is a list of matrices with the estimated
          random effects for each level of grouping. For each matrix in
          the 'random' list, the columns refer to the random effects
          and the rows to the groups.

contrasts: a list with the contrasts used to represent factors in the
          fixed effects formula  and/or random effects 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 nlme model, this
          component will be an empty list.

    dims: a list with basic dimensions used in the nlme fit, including
          the components 'N' - the number of observations in the data,
          'Q' - the number of grouping levels, 'qvec' - the number of
          random effects at each level from innermost to outermost
          (last two values are equal to zero and correspond to the
          fixed effects and the response), 'ngrps' - the number of
          groups at each level from innermost to outermost (last two
          values are one and correspond to the fixed effects and the
          response), and 'ncol' - the number of columns in the model
          matrix for each level of grouping from innermost to outermost
          (last two values are equal to the number of fixed effects and
          one).

  fitted: a data frame with the fitted values as columns. The leftmost
          column corresponds to the population fixed effects
          (corresponding to the fixed effects only) and successive
          columns from left to right correspond to increasing levels of
          grouping.

   fixDF: a list with components 'X' and 'terms' specifying the
          denominator degrees of freedom for, respectively, t-tests for
          the individual fixed effects and F-tests for the
          fixed-effects terms in the models.

  groups: a data frame with the grouping factors as columns. The
          grouping level increases from left to right.

  logLik: the (restricted) log-likelihood at convergence.

     map: a list with components 'fmap', 'rmap', 'rmapRel', and 'bmap',
          specifying various mappings for the fixed and random effects,
          used to generate predictions from the fitted object.

  method: the estimation method: either '"ML"' for maximum likelihood,
          or '"REML"' for restricted maximum likelihood.

modelStruct: an object inheriting from class 'nlmeStruct', representing
          a list of mixed-effects model components, such as 'reStruct',
          'corStruct', and 'varFunc' objects.

 numIter: the number of iterations used in the iterative algorithm.

residuals: a data frame with the residuals as columns. The leftmost
          column corresponds to the population residuals and successive
          columns from left to right correspond to increasing levels of
          grouping.

   sigma: the estimated within-group error standard deviation.

  varFix: an approximate covariance matrix of the fixed effects
          estimates.

_A_u_t_h_o_r(_s):

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

_S_e_e _A_l_s_o:

     'nlme', 'nlmeStruct'

