plot.profile.nls {stats} | R Documentation |
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
.
## S3 method for class 'profile.nls': plot(x, levels, conf= c(99, 95, 90, 80, 50)/100, nseg = 50, absVal =TRUE, ...)
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). |
nseg |
an integer value giving the number of segments to use in the spline interpolation of the profile t curves. Defaults to 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 . |
... |
other arguments to the plot function can be passed here. |
Douglas M. Bates and Saikat DebRoy
Bates, D.M. and Watts, D.G. (1988), Nonlinear Regression Analysis and Its Applications, Wiley (chapter 6)
# 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)