Thanks a lot, this I(xx^2) ... worked.
I guess, I should learn more abot the function poly itself. (so will I... :)
)
Thanks again!
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On 12/08/2010 10:35 AM, szisziszilvi wrote:
I've tried lm, but something is wrong.
I've made a test dataset of 599 data points, my original equation is
zz = 1 +0.5*xx -3.2*xx*xx -1*yy +4.2*yy*yy
but the R gives this result:
---
> mp <- read.cs
right. How does it come that if I devide the result vector with
10*interception, I get a much better result?
> zz2 <- 25.86 -2239.86*mp$xx -595.01*mp$xx*mp$xx + 2875.54*mp$yy +
> 776.84*mp$yy*mp$yy
> mp$zz2 <- zz2
> library(lattice)
> cloud(zz2/258.6 + zz ~ xx * yy, data=mp)
looks quite pretty.
I've tried lm, but something is wrong.
I've made a test dataset of 599 data points, my original equation is
zz = 1 +0.5*xx -3.2*xx*xx -1*yy +4.2*yy*yy
but the R gives this result:
---
> mp <- read.csv(file="sample.csv",sep=";",header=TRUE)
> lm
oh, god, please don't tell anybody...
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On 11/08/2010 6:15 AM, szisziszilvi wrote:
Hello!
Is there a simplier way in R to get a nonlinear regression (like nls) for a
surface? I have 3D data, and it is definitely not a linear surface with
which it would fit the best. Rather sg like z = a + f(x) + g(y) where
probably both f and g are po
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