# plot.profile.nls

##### Plot a profile.nls Object

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`

.

- Keywords
- models, regression, nonlinear

##### Usage

`"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.

##### References

Bates, D.M. and Watts, D.G. (1988),
*Nonlinear Regression Analysis and Its Applications*,
Wiley (chapter 6)

##### See Also

##### Examples

`library(stats)`

```
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)
```

*Documentation reproduced from package stats, version 3.2.2, License: Part of R 3.2.2*

### Community examples

Looks like there are no examples yet.