Closed cbird808 closed 4 years ago
Hello,
thanks for your comment. I noted that the optimisation algorithm in 'nls()' is often more efficient tan that in 'drm()'. If necessary, I am also providing a self starter for nls(), that is NLS.powerCurve(). The code below appears to work properly
library(aomisc)
library(lattice)
x <- c(100, 500, 1000, 5000, 10000)
y <- c(1.61E-05, 2.88E-06, 1.38E-06, 2.27E-07, 1.21E-07)
llModel.coef.e <- nls(y ~ NLS.powerCurve(x, a, b))
summary(llModel.coef.e)
plotnls(llModel.coef.e)
All the best
Andrea
when fitting the following data:
x | y 100 | 1.61E-05 500 | 2.88E-06 1000 | 1.38E-06 5000 | 2.27E-07 10000 | 1.21E-07
The parameters are far from fitting the data.
With nls the result is a much much better fit: