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Thread: Calculation of parameter uncertainties when using method of least squares

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    Calculation of parameter uncertainties when using method of least squares




    Hi everyone,

    I am struggling with a maybe simple problem. I have a set of data points (x,y) for which I would like to derive a fitting function of a given type. This fitting function shall read:

    y = A * ( B + C * x )^(-0.5)

    with A, B, and C being the free parameters of the fitting function. I am using a quick'n'dirty approach using least squares to find the fitting function, i.e. I am running loops over A, B, and C from some minimum to maximum value for the parameters and a specified range of x. For each combination, I calculate the square error (hence least squares...) based on all data points. The combination with the least square error then is my desired fitting function.

    This method works and I have processed my data successfully. Now, somebody asked me whether I could provide uncertainty ranges for A,B, and C, say I shall provide A=1.5+-0.3 etc.. But I can't imagine how to do it.

    I would be glad to get some help on how to derive these uncertainties

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    Re: Calculation of parameter uncertainties when using method of least squares


    I feel like bumping this! I still have hope that you statistics experts can help me out... and it's becoming urgent...

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