Sebastian Leuzinger wrote:
Dear R
I would like to predict x-values in a 4th order polynomial regression:
x <- c(1:10) y <- c(2,7,19,49,89,94,97,98,92,89) # these are percentages
lm(y ~ x+I(x^2)+I(x^3)+I(x^4)-1) -> lm1
now I would like to know what the model fit (x-value) for y=50 is. This results in solving a 4th order quadratic equation. polyroot() does not really help because it only gives me the x-values for y=0. I have tried with nls() which sort of works, but I am sure there is a much easier solution to that, can anyone give me a hint?
What about optim()?
Uwe Ligges
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