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## Main Question or Discussion Point

Dear all,

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

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)

I need to know, for any parameter Tj, the mean and variance of this error

Thank you in advance

Cmunikat

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 error

**ef(Tj)**, in terms of the mean and variance of the measurement errors "e(Ti,mi)" defined at the beggining.Thank you in advance

Cmunikat