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, D. M. and Watts, D. G. (1988), Nonlinear Regression Analysis and Its Applications, Wiley (chapter 6).

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
## IGNORE_RDIFF_BEGIN
pr1$A pr1$lrc
## IGNORE_RDIFF_END