nlsList.selfStart            package:nlme            R Documentation

nlsList Fit from a selfStart Function

Description:

     The response variable and primary covariate in 'formula(data)' are
     used together with 'model' to construct the nonlinear model
     formula. This is used in the 'nls' calls and, because a
     selfStarting model function can calculate initial estimates for
     its parameters from the data, no starting estimates need to be
     provided.

Usage:

     ## S3 method for class 'selfStart':
     nlsList(model, data, start, control, level, subset, na.action, pool)

Arguments:

   model: a 'selfStart' model function, which calculates initial
          estimates for the model parameters from 'data'.

    data: a data frame in which to interpret the variables in 'model'.
          Because no grouping factor can be specified in 'model',
          'data' must inherit from class 'groupedData'.  

   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. 

Value:

     a list of 'nls' objects with as many components as the number of
     groups defined by the grouping factor. A 'NULL' value is assigned
     to the components corresponding to clusters for which the 'nls'
     algorithm failed to converge. 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.

See Also:

     'selfStart', 'groupedData', 'nls', 'nlsList', 'nlme.nlsList',
     'nlsList.formula'

Examples:

     fm1 <- nlsList(SSasympOff, CO2)
     summary(fm1)

