profile.nls

0th

Percentile

Method for Profiling nls Objects

Investigates the profile log-likelihood function for a fitted model of class "nls".

Keywords
models, regression, nonlinear
Usage
## S3 method for class 'nls':
profile(fitted, which = 1:npar, maxpts = 100, alphamax = 0.01,
        delta.t = cutoff/5, \dots)
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.valsa matrix of parameter values for each fitted model.
  • tauthe profile t-statistics.

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

Aliases
  • profile.nls
Examples
library(stats) <testonly>od <- options(digits = 4)</testonly> # 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, alpha = 0.05) # profiled values for the two parameters pr1$A pr1$lrc # see also example(plot.profile.nls) <testonly>options(od)</testonly>
Documentation reproduced from package stats, version 3.3, License: Part of R 3.3

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