profile.nls
Method for Profiling nls Objects
Investigates the profile log-likelihood 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 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.
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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