ellipse.profile {ellipse} | R Documentation |
This routine approximates a contour of a function based on the profile of that function.
ellipse.profile(x, which=c(1, 2), level=0.95, t=sqrt(qchisq(level, 2)), npoints=100)
x |
An object of class profile, typically the result of the profile() function applied to a fit by the ms() general maximum likelihood procedure. |
which |
Which pair of parameters to use. |
level |
Assuming that the function is -2 times the log likelihood of a regular model, this specifies the confidence level for an asymptotic confidence region. |
t |
The square root of the value to be contoured. |
npoints |
How many points to use in the ellipse. |
This function uses the 4 point approximation to the contour as described in Appendix 6 of Bates and Watts. It produces the exact contour for quadratic surfaces, and good approximations for mild deviations from quadratic. If the surface is multimodal, the algorithm is likely to produce nonsense.
An npoints x 2 matrix with columns having the chosen parameter names, which approximates a contour of the function that was profiled.
Bates and Watts (1988) Nonlinear Regression Analysis & its Applications
profile, ms, ellipse.nls
# Plot an approximate 95% confidence region for the Puromycin # parameters Vm and K, and overlay the ellipsoidal region data(Puromycin) Purboth <- nls(formula = rate ~ ((Vm + delV * (state == "treated")) * conc)/(K + conc), data = Puromycin, start = list(Vm = 160, delV = 40, K = 0.05)) Pur.prof <- profile(Purboth) plot(ellipse(Pur.prof,which=c('Vm','K')),type='l') lines(ellipse(Purboth,which=c('Vm','K')),lty=2)