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I have a set of measurements {xm(Ti,mi)=x(Ti)+e(Ti,mi)}, where:

_xm is the measured value

_x is the actual value

_e is a random measurement error for the measurement mi

_Ti is a parameter

I need to fit a curve to this data by some method. For example, if I use least squares best fit, the following value D is minimized:

D=Ʃ Di^{2}

Where:

_Di=X(T=Ti)-xm(Ti)

_X is the continuous curve

Now, I define the error between the curve X(T) and the actual data x(Ti):

ef(Ti) = X(T) - x(Ti)

And here is the problem:

I need to know, for any parameter Tj, the mean and variance of this erroref(Tj), in terms of the mean and variance of the measurement errors "e(Ti,mi)" defined at the beggining.

Thank you in advance

Cmunikat

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# Fitted curve to measured data - statistical properties of the fit error

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