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).

### 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)
```

*stats*version 4.4.0 Index]