Polynomial fitting
Thank you Gerrit for the quick reply! And yes, i'm Matti. I can get the coeffs now, though i'm not sure whether i'm doing something wrong or whether poly is just not the right method for what i'm trying to find. I will look into this more closely and give it another try. Is poly best for fitting on noisy data that's been generated by a polynomial and not that good for approximating an arbitrary function? I tried a least squares fitting with a web applet and got all exited because the approximation looked quite promising. I understand that R is designed mainly for statistical computing and may not be the best tool for my purposes. Before i look elsewhere i would like to ask if there is some other R method i should try, perhaps a least squares approximation? Thank you for your help! Matti Jokipii 08.07.2011 08:25, Gerrit Eichner kirjoitti:
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: http://r.789695.n4.nabble.com/Polynomial-fitting-tp3652816p3652816.html Sent from the R help mailing list archive at Nabble.com.
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