profile.nls              package:stats              R Documentation

Method for Profiling nls Objects

Description:

     Investigates the profile log-likelihood function for a fitted
     model of class '"nls"'.

Usage:

     ## S3 method for class 'nls':
     profile(fitted, which = 1:npar, maxpts = 100, alphamax = 0.01,
             delta.t = cutoff/5, ...)

Arguments:

  fitted: the original fitted model object.

   which: the original model parameters which should be profiled. This
          can be a numeric or character vector. By default, all
          non-linear parameters are profiled.

  maxpts: maximum number of points to be used for profiling each
          parameter.

alphamax: highest significance level allowed for the profile
          t-statistics.

 delta.t: suggested change on the scale of the profile t-statistics. 
          Default value chosen to allow profiling at about 10 parameter
          values.

     ...: further arguments passed to or from other methods.

Details:

     The profile t-statistics is defined as the square root of change
     in sum-of-squares divided by residual standard error with an
     appropriate sign.

Value:

     A list with an element for each parameter being profiled. The
     elements are data-frames with two variables  

par.vals: a matrix of parameter values for each fitted model.

     tau: the profile t-statistics.

Author(s):

     Of the original version,  Douglas M. Bates and Saikat DebRoy

References:

     Bates, D. M. and Watts, D. G. (1988), _Nonlinear Regression
     Analysis and Its Applications_, Wiley (chapter 6).

See Also:

     'nls', 'profile', 'plot.profile.nls'

Examples:

     # obtain the fitted object
     fm1 <- nls(demand ~ SSasympOrig(Time, A, lrc), data = BOD)
     # get the profile for the fitted model: default level is too extreme
     pr1 <- profile(fm1, alpha = 0.05)
     # profiled values for the two parameters
     pr1$A
     pr1$lrc
     # see also example(plot.profile.nls)

