plot.profile.nls {stats} | R Documentation

## Plot a profile.nls Object

### Description

Displays a series of plots of the profile t function and interpolated confidence intervals for the parameters in a nonlinear regression model that has been fit with `nls` and profiled with `profile.nls`.

### Usage

    ## S3 method for class 'profile.nls'
    plot(x, levels, conf = c(99, 95, 90, 80, 50)/100,
         absVal = TRUE, ylab = NULL, lty = 2, ...)

### Arguments

`x` | an object of class `"profile.nls"`
`levels` | levels, on the scale of the absolute value of a t statistic, at which to interpolate intervals. Usually `conf` is used instead of giving `levels` explicitly.
`conf` | a numeric vector of confidence levels for profile-based confidence intervals on the parameters. Defaults to `c(0.99, 0.95, 0.90, 0.80, 0.50).`
`absVal` | a logical value indicating whether or not the plots should be on the scale of the absolute value of the profile t. Defaults to `TRUE`.
`lty` | the line type to be used for axis and dropped lines.
`ylab, ...` | other arguments to the `plot.default` function can be passed here (but not `xlab`, `xlim`, `ylim` nor `type`).

### Details

The plots are produced in a set of hard-coded colours, but as these are coded by number their effect can be changed by setting the `palette`. Colour 1 is used for the axes and 4 for the profile itself. Colours 3 and 6 are used for the axis line at zero and the horizontal/vertical lines dropping to the axes.

### 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`, `profile.nls`

### Examples

    require(graphics)

    # obtain the fitted object
    fm1 <- nls(demand ~ SSasympOrig(Time, A, lrc), data = BOD)
    # get the profile for the fitted model
    pr1 <- profile(fm1, alpha = 0.05)
    opar <- par(mfrow = c(2,2), oma = c(1.1, 0, 1.1, 0), las = 1)
    plot(pr1, conf = c(95, 90, 80, 50)/100)
    plot(pr1, conf = c(95, 90, 80, 50)/100, absVal = FALSE)
    mtext("Confidence intervals based on the profile sum of squares",
          side = 3, outer = TRUE)
    mtext("BOD data - confidence levels of 50%, 80%, 90% and 95%",
          side = 1, outer = TRUE)
    par(opar)

[Package stats version 3.3.2 Index]