Hello everyone,
well, I'm trying to fit my data corresponding to points of the contour of a
circle to a model. the problem I have is, as I have data for a circle, I
have negative and positive values for the radius. So the model has to fit
for both values. I want from this fitting data process to find out the
coefficients of my model the permit to approach the max possible to the true
values of the radius.
I've tried two methods: I used the function "leasqr" from the Octave package
"optim", and I used the function "fmin" to search the min of the sum of the
squared errors.
the problem with the two methods is that I have to separate my data into two
sets: negative and positive, which cause different values of coefficients
(which is not what I'm seeking).
Another problem is that I want to calculate the best coefficients so my data
be the nearest possible to the nominal value, which I don't know how to do
it; when I use "leasqr" it gives me the number of iterations and the final
parameters, but I want to know the parameters calculated at each iteration
and continue until having the best ones.
please find attached two plots to understand the problem (the fitted plot is
far from the nominal value 10)
I'll appreciate any help you could provide me
<http://octave.1599824.n4.nabble.com/file/t373159/fitting_with_leasqr.png>
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Sent from: http://octave.1599824.n4.nabble.com/Octave-General-f1599825.html
If you convert your numbers tp polar coordinates then you would have a radius and an angle. the radius would always be positive.
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DAS