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, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ [EMAIL PROTECTED] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
