Method for Profiling nls Objects
Investigates the profile log-likelihood function for a fitted model of
# S3 method for nls profile(fitted, which = 1:npar, maxpts = 100, alphamax = 0.01, delta.t = cutoff/5, …)
- the original fitted model object.
- the original model parameters which should be profiled. This can be a numeric or character vector. By default, all non-linear parameters are profiled.
- maximum number of points to be used for profiling each parameter.
- highest significance level allowed for the profile t-statistics.
- 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.
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.
A list with an element for each parameter being profiled. The elements are data-frames with two variables
Bates, D. M. and Watts, D. G. (1988), Nonlinear Regression Analysis and Its Applications, Wiley (chapter 6).
# 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)