ellipse.nls {ellipse} | R Documentation |
This function produces the ellipsoidal outline of an approximate pairwise confidence region for a nonlinear model fit.
ellipse.nls(x, which=c(1, 2), level=0.95, t=sqrt(2 * qf(level, 2, s$df[2])), ...)
x |
The first argument should be an nls object, usually resulting from a call to nls(). |
which |
Which selects the pair of parameters to be plotted. The default is the first two. |
level |
The confidence level of the region. Default 95%. |
t |
The t statistic on the boundary of the ellipse. |
... |
Other ellipse.default parameters may also be used. |
The summary function is used to obtain the approximate covariance matrix of the fitted parameters.
A matrix with columns x and y to outline the confidence region.
ellipse.default, ellipse.profile
# Plot an approximate 95% confidence region for the weight and displacement # parameters in the Michaelis Menten model conc <- c(0.3330, 0.1670, 0.0833, 0.0416, 0.0208, 0.0104, 0.0052) vel <- c(3.636, 3.636, 3.236, 2.666, 2.114, 1.466, 0.866) Micmen <- data.frame(conc=conc, vel=vel) fit <- nls(vel~Vm*conc/(K+conc),Micmen,start=list(K=0.02,Vm=3.7)) plot(ellipse(fit))