| profiler.nls {stats} | R Documentation |
Create a profiler object for the model object fitted of class
nls.
## S3 method for class 'nls': profiler(fitted, ...)
fitted |
the original fitted model object of class
nls. |
... |
Additional parameters. None are used. |
An object of class profiler.nls which is a list with function
elements
getFittedModel() |
the nlsModel object corresponding to fitted
|
getFittedPars() |
See documentation for profiler
|
setDefault(varying, params) |
See documentation for profiler
|
getProfile(varying, params) |
In the returned list, fstat is the ratio of change in
sum-of-squares and the residual standard error.
For other details, see documentation for profiler
|
When using setDefault and getProfile together, the internal state of
the fitted model may get changed. So after completing the profiling
for a parameter, the internal states should be restored by a call to
setDefault without any arguments. For example see below or the source
for profile.nls.
Douglas M. Bates and Saikat DebRoy
Bates, D.M. and Watts, D.G. (1988), Nonlinear Regression Analysis and Its Applications, Wiley
nls,
nlsModel,
profiler,
profile.nls
data( BOD ) ## obtain the fitted object fm1 <- nls(demand ~ SSasympOrig( Time, A, lrc ), data = BOD) ## get the profile for the fitted model prof1 <- profiler( fm1 ) ## profile with A fixed at 16.0 prof1$getProfile(c(FALSE, TRUE), 16.0) ## vary lrc prof1$setDefault(varying = c(FALSE, TRUE)) ## fix A at 14.0 and starting estimate of lrc at -0.2 prof1$setDefault(params = c(14.0, -0.2)) ## and get the profile prof1$getProfile() ## finally, set defaults back to original estimates prof1$setDefault()