stats (version 3.4.1)

plot.profile.nls: 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 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.

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)