# Find coefficients for a unified model for fitting negative and positive output

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## Find coefficients for a unified model for fitting negative and positive output

 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 -- Sent from: http://octave.1599824.n4.nabble.com/Octave-General-f1599825.html
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## Re: Find coefficients for a unified model for fitting negative and positive output

 On Tue, Jan 29, 2019 at 5:25 PM insafba <[hidden email]> wrote: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 -- 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.-- DAS
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## Re: Find coefficients for a unified model for fitting negative and positive output

 Thank you for replying, actually, this is what I did, but when I assume that the radius values are positive, I get a completely messy figure as below. but that's doesn't matter. the problem is how to approach the max possible to the true value (which is in my case 10) and how to recalculate the coefficients by successive iterations until finding a satisfying result? -- Sent from: http://octave.1599824.n4.nabble.com/Octave-General-f1599825.html
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## Re: Find coefficients for a unified model for fitting negative and positive output

 On Wed, Jan 30, 2019, 6:47 AM insafba <[hidden email] wrote:Thank you for replying, actually, this is what I did, but when I assume that the radius values are positive, I get a completely messy figure as below. but that's doesn't matter. the problem is how to approach the max possible to the true value (which is in my case 10) and how to recalculate the coefficients by successive iterations until finding a satisfying result? -- Sent from: http://octave.1599824.n4.nabble.com/Octave-General-f1599825.htmlIf your true data is a circle , then the radius is a constant and  should show up as a horizontal straight line.Do you think  that the true radius is 10?If you want to find a horizontal straight line you could put six or seven copies of your raw data end to end and then do a normal straight line approximation and see what you get.You're raw data sure doesn't look like it's part of a pure Circle