| profile.nls {stats} | R Documentation |
Method for Profiling nls Objects
Description
Investigates the profile log-likelihood function for a fitted model of
class "nls".
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. 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. |
Author(s)
Of the original version, Douglas M. Bates and Saikat DebRoy
References
Bates DM, Watts DG (1988).
Nonlinear Regression Analysis and Its Applications, series Wiley Series in Probability and Statistics.
Wiley.
ISBN 9780471816430.
Chapter 6.
See Also
nls, profile, plot.profile.nls
Examples
# 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, alphamax = 0.05)
# profiled values for the two parameters
pr1$A
pr1$lrc
# see also example(plot.profile.nls)