MATLAB: Limiting coeficients in fitting function.

coefficientcurve fittingfitfitoptionsfittype

I need to make one of coefficients in my model function stricte positive number to avoid complex results. Is there any possibility to limit my coefficient?

Best Answer

Square the coefficient in your model.

Best wishes

Torsten.

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MATLAB: Matlab curve fitting tool automation for selection of fit with minimum sse.

You could certainly write your own function by using the gof output of the "fit" function.

Here is an example that shows you how to use the "fit" to see the Goodness of Fit of different methods. You could store the "gof" values in an array and find the max GoF.

function bestFitName = Gof_Finder( x, y )
    Fits = {'poly1', 'poly2', 'poly3', 'exp1'};
      for i=1:numel(Fits)
          [~,GoFs(i)] = fit( x, y,  Fits{i} );
      end
      [~, minIdx] = min([GoFs.sse]);
      bestFitName = Fits{minIdx};
  end

The above function will return the name of the best fit of the data x and y.

MATLAB: Curve fitting: What does LAR do

I don't understand what is confusing. The sum of the absolute values of the residuals is clearly NOT least squares, thus a minimum sum of squares of residuals. If it was, there would be no point in offering it as an alternative.

Least squares puts more importance on the large residuals. For example, suppose you have two cases, based on two sets of parameters. We need consider only two points.

Case 1: Resid1 = 1, Resid2 = 1
case 2: Resid1 = 0, Resid2 = 2

For a least squares solver, the two cases are very different. Case 1 would be preferred, since the sum of squares is 2, versus 4 for the latter. So whatever set of parameters generated case 1 will be chosen as better.

In a LAR scheme (also called MAD, for minimum absolute deviations) the sum of the absolute residuals are identical. Neither solution would be preferred over the other.

One reason one might use such a scheme is it will be less sensitive to outliers in the data, whereas least squares tends to be jerked around by outliers quite easily.

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Related Solutions

MATLAB: Matlab curve fitting tool automation for selection of fit with minimum sse.

MATLAB: Curve fitting: What does LAR do

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