Re: [R] easy way to do a 2-D fit to an array of data?

From: Ravi Varadhan <rvaradhan_at_jhmi.edu>
Date: Mon, 02 May 2011 22:08:01 -0400

You may want to consider spatial::surf.ls

Or, a simplistic approach where you fit a model such as using `lm':

E[Z | x, y] = a + b(x - x0)^2 + c(y - y0)^2

where (x0, y0) is the location of maximum.

Ravi.



From: r-help-bounces_at_r-project.org [r-help-bounces_at_r-project.org] On Behalf Of Carl Witthoft [carl_at_witthoft.com] Sent: Monday, May 02, 2011 7:14 PM
To: r-help_at_r-project.org
Subject: [R] easy way to do a 2-D fit to an array of data?

Hi,
I've got a matrix, Z, of values representing (as it happens) optical power at each pixel location. Since I know in advance I've got a single, convex peak, I would like to do a 2D parabolic fit of the form Z = poly((x+y),2) where x and y are the x,y coordinates of each pixel (or equivalently, the row, column numbers). Is there an R function that lets me easily implement that? I've started down the path of something like

zvec <- as.vector(Z), and creating applicable x,y vectors by something like (where for the sake of argument Z is 128x128)

foo<-matrix(seq(1,128),128,128)

xvec <- as.vector(foo)
yvec <- as.vector(t(foo))

at which point I can feed zvec, xvec, yvec to lm() .

I'm hopeful someone can point me to a much easier way to do the same thing. Oh, and if there's a 2-D splinefunction generator, that would work for me as well.

thanks
Carl



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