profile.nls {stats} | 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

# 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

[Package

*stats* version 2.2.1

Index]