1. The question of "linear" vs. "nonlinear" means "linear in the
parameters to be estimated. All the examples you have given so far are
linear in the parameters to be estimated. The fact that they are
nonlinear in "x" is immaterial.
2. With this hint and the posting guide
"http:
Dear all
Here is a hopefully better example with regards to
nonlinear robust fitting:
# fitting a polynomial:
x <- seq(-10,10,0.2)
y <- 10*x + 4*x*x - 2*x*x*x
plot(x,y)
z <- jitter(y,amount=300)
plot(x,z)
df <- as.data.frame(cbind(x,z))
nf <- nls(z ~ a*x + b*x*x + c*x*x*x, data=df,
+ sta
