That's pretty standard. Some call it "response surface analysis". Of course you
need to check assumptions like homoscedasticity on the log scale, etc.
It's not really an R question, specifically; so stats.stackexchange.com is a
better avenue for more detailed discussions. As far as R goes, you just need to
be aware that, due to an ancien misfeature, terms like x^2 need to be protected
by writing I(x^2).
-pd
On 23 Feb 2016, at 11:42 , <james.fo...@diamond.ac.uk>
<james.fo...@diamond.ac.uk> wrote:
> Dear R community,
> this is probably a well-known topic to some of you, but I am not well into it
> and would like some clarifications or even jus some suggestions.
>
> I have a quadratic scalar field:
>
> F(x,y)=K*exp(-(a*x^2+b*y^2+c*x*y))
>
> I also have a random set of positive x,y values and related F(x,y) values.
> It seems reasonable to estimate the parameters K, a, b, c with a linear
> regression,
> using the log of both sides of the equation.
>
> What worries me, though, is the interaction term, c*x*y.
>
> Are there well-known issues on the application of linear regression to cases
> like this one?
>
> Thanks in advance for your answers.
>
> James
>
> --
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>
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--
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Office: A 4.23
Email: pd....@cbs.dk Priv: pda...@gmail.com
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