nlsList                 package:nlme                 R Documentation

_L_i_s_t _o_f _n_l_s _O_b_j_e_c_t_s _w_i_t_h _a _C_o_m_m_o_n _M_o_d_e_l

_D_e_s_c_r_i_p_t_i_o_n:

     'Data' is partitioned according to the levels of the grouping
     factor defined in 'model' and individual 'nls' fits are obtained
     for each 'data' partition, using the model defined in 'model'.

_U_s_a_g_e:

     nlsList(model, data, start, control, level, subset, na.action, pool)
     ## S3 method for class 'nlsList':
     update(object, model., ..., evaluate = TRUE)

_A_r_g_u_m_e_n_t_s:

  object: an object inheriting from class 'nlsList', representing a
          list of fitted 'nls' objects.

   model: either a nonlinear model formula, with the response on the
          left of a '~' operator and an expression involving
          parameters, covariates, and a grouping factor separated by
          the '|' operator on the right, or a 'selfStart' function. 
          The method function 'nlsList.selfStart' is documented
          separately. 

  model.: Changes to the model - see 'update.formula' for details.

    data: a data frame in which to interpret the variables named in
          'model'. 

   start: an optional named list with initial values for the parameters
          to be estimated in 'model'. It is passed as the 'start'
          argument to each 'nls' call and is required when the
          nonlinear function in 'model' does not inherit from class
          'selfStart'. 

 control: a list of control values passed as the 'control' argument to
          'nls'. Defaults to an empty list. 

   level: an optional integer specifying the level of grouping to be
          used when multiple nested levels of grouping are present.

  subset: an optional expression indicating the subset of the rows of
          'data' that should be used in the fit. This can be a logical
          vector, or a numeric vector indicating which observation
          numbers are to be included, or a  character  vector of the
          row names to be included.  All observations are included by
          default.

na.action: a function that indicates what should happen when the data
          contain 'NA's.  The default action ('na.fail') causes
          'nlsList' to print an error message and terminate if there
          are any incomplete observations. 

    pool: an optional logical value that is preserved as an attribute
          of the returned value.  This will be used as the default for
          'pool' in calculations of standard deviations or standard
          errors for summaries. 

     ...: some methods for this generic require additional arguments. 
          None are used in this method.

evaluate: If 'TRUE' evaluate the new call else return the call.

_V_a_l_u_e:

     a list of 'nls' objects with as many components as the number of
     groups defined by the grouping factor. Generic functions such as
     'coef', 'fixed.effects', 'lme', 'pairs', 'plot', 'predict',
     'random.effects', 'summary', and 'update' have methods that can be
     applied to an 'nlsList' object.

_R_e_f_e_r_e_n_c_e_s:

     Pinheiro, J.C., and Bates, D.M. (2000), _Mixed-Effects Models in S
     and S-PLUS_, Springer.

_S_e_e _A_l_s_o:

     'nls', 'nlme.nlsList', 'nlsList.selfStart',  'summary.nlsList'

_E_x_a_m_p_l_e_s:

     fm1 <- nlsList(uptake ~ SSasympOff(conc, Asym, lrc, c0),
        data = CO2, start = c(Asym = 30, lrc = -4.5, c0 = 52))
     summary(fm1)