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I have some data, approximately 6 months worth. It is values that do not depend on time but are represented by a pair (x, y) such that the values x is measured at a point in time y. Therefore the data is equivalent to measuring how much stock I have in a given time period, say. The measurements occur once a day for 6 months.

I need to take this data and create a model that would allow me to predict values of x in (say) one month, three months and six months time.

My question is what is the best method to use? Should I suupose that a power law exists and us a regression model, or would a simple plotting of moving averages allow me to make an accurate prediction?

I guess I don't necessarily need to end with a function model representing x ans a function of y (x = f(y)) but more that I can use some statistical inference to accurately forecast the values of x_{i} in the future.

Any help on this matter would be very appreciated.

Regards,

kdbnlin

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# Best model to fit data

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