\Header{plot.profile.nls}{Plot a profile.nls Object}
\keyword{nonlinear}{plot.profile.nls}
\keyword{regression}{plot.profile.nls}
\keyword{models}{plot.profile.nls}
\begin{Description}\relax
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 \code{nls} and profiled with
\code{profile.nls}.\end{Description}
\begin{Usage}
\begin{verbatim}
plot.profile.nls(x, levels, conf, nseg, absVal, ...)
\end{verbatim}
\end{Usage}
\begin{Author}\relax
Douglas M. Bates and Saikat DebRoy\end{Author}
\begin{References}\relax
Bates, D.M. and Watts, D.G. (1988), \emph{Nonlinear Regression Analysis
and Its Applications}, Wiley (chapter 6)\end{References}
\begin{SeeAlso}\relax
\code{\Link{nls}}, \code{\Link{profile}}, \code{\Link{profile.nls}}\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
library( nls )
data( BOD )
# obtain the fitted object
fm1 <- nls(demand ~ SSasympOrig( Time, A, lrc ), data = BOD)
# get the profile for the fitted model
pr1 <- profile( fm1 )
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)
\end{ExampleCode}
\end{Examples}

