Hello, mfa (Matti?),
if x and y contain the coordinates of your data points and k is the wanted
polynomial degree, then
fit <- lm( y ~ poly( x, k))
fits orthonormal polynomials up to degree k to your data. Using
dummy.coef( fit)
should give the coefficients you are interested in.
Hth -- Gerrit
On Thu, 7 Jul 2011, mfa wrote:
> Hello,
>
> i'm fairly familiar with R and use it every now and then for math
related
> tasks.
>
> I have a simple non polynomial function that i would like to approximate
> with a polynomial. I already looked into poly, but was unable to understand
> what to do with it. So my problem is this. I can generate virtually any
> number of datapoints and would like to find the coeffs a1, a2, ... up to a
> given degree for a polynomial a1x^1 + a2x^2 + ... that approximates my
> simple function. How can i do this with R?
>
> Your help will be highly appreciated!
>
> --
> View this message in context:
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> Sent from the R help mailing list archive at Nabble.com.
>
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