| profile.nls {nls} | R Documentation |
Method for Profiling nls Objects
Description
Investigates behavior of the log-likelihood function near the solution
represented by fitted.
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. By default, all parameters are profiled. |
maxpts |
maximum number of points to be used for profiling each parameter. |
alphamax |
maximum 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)
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,
profiler.nls, plot.profile.nls
Examples
data( BOD )
# obtain the fitted object
fm1 <- nls(demand ~ SSasympOrig( Time, A, lrc ), data = BOD)
# get the profile for the fitted model
pr1 <- profile( fm1 )
# profiled values for the two parameters
pr1$A
pr1$lrc