% File src/library/stats/man/plot.profile.nls.Rd % Part of the R package, https://www.R-project.org % Copyright 1995-2011 R Core Team % Distributed under GPL 2 or later \name{plot.profile.nls} \alias{plot.profile.nls} \title{Plot a \code{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 \code{nls} and profiled with \code{profile.nls}. } \usage{ \method{plot}{profile.nls}(x, levels, conf = c(99, 95, 90, 80, 50)/100, absVal = TRUE, ylab = NULL, lty = 2, \dots) } \arguments{ \item{x}{an object of class \code{"profile.nls"} } \item{levels}{levels, on the scale of the absolute value of a t statistic, at which to interpolate intervals. Usually \code{conf} is used instead of giving \code{levels} explicitly.} \item{conf}{a numeric vector of confidence levels for profile-based confidence intervals on the parameters. Defaults to \code{c(0.99, 0.95, 0.90, 0.80, 0.50).}} \item{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 \code{TRUE}.} \item{lty}{the line type to be used for axis and dropped lines.} \item{ylab, \dots}{other arguments to the \code{\link{plot.default}} function can be passed here (but not \code{xlab}, \code{xlim}, \code{ylim} nor \code{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 \code{\link{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), \emph{Nonlinear Regression Analysis and Its Applications}, Wiley (chapter 6) } \author{Douglas M. Bates and Saikat DebRoy} \seealso{ \code{\link{nls}}, \code{\link{profile}}, \code{\link{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, alphamax = 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) } \keyword{nonlinear} \keyword{regression} \keyword{models}