[R] predicting x values in a polynomial regression

[Prof Brian Ripley]

On Wed, 27 Oct 2004, Sebastian Leuzinger wrote:

> 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.

And what are the roots of p(x) - 50?

> 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?

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
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