R: Method for Profiling nls Objects

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

    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

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