profile.nls
Method for Profiling nls Objects
Investigates the profile loglikelihood function for a fitted model of
class "nls"
.
 Keywords
 models, regression, nonlinear
Usage
"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 nonlinear parameters are profiled.
 maxpts
 maximum number of points to be used for profiling each parameter.
 alphamax
 highest significance level allowed for the profile tstatistics.
 delta.t
 suggested change on the scale of the profile tstatistics. Default value chosen to allow profiling at about 10 parameter values.
 ...
 further arguments passed to or from other methods.
Details
The profile tstatistics is defined as the square root of change in sumofsquares divided by residual standard error with an appropriate sign.
Value

A list with an element for each parameter being profiled. The elements
are dataframes with two variables
 par.vals
 a matrix of parameter values for each fitted model.
 tau
 the profile tstatistics.
References
Bates, D. M. and Watts, D. G. (1988), Nonlinear Regression Analysis and Its Applications, Wiley (chapter 6).
See Also
Examples
library(stats)
# 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)
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