[EMAIL PROTECTED] (Tugba Taskaya) wrote in message news:<[EMAIL PROTECTED]>... > It says that a(t) should be independently distributed as normal random > variables with mean=0. So can't I find an initial residual that makes > the mean of the residuals 0?
This means that after you compute the a(14),a(15),......a(t) you need to test the the ACF ( autocorrelation ) of these values has no significant structure .... and that the mean of the a's is zero everyhere ( i.e. for all contiguous subsets ) otherwise you need to introduce dummy variables to deaal with this Gaussian violation ( Pulse,Step, Seasonal Pulse and/or Local Time Trends ) and that the variance of the a's is constant over time and that the estimated parameter(s) (thetha 1 in your case) is constant over time. > > On the paper, they say that they aim to take first-order regular > difference and the first seasonal difference in order to remove the > growth trend and the seasonality characteristics. So they say ! Observing non-stationarity is one thing ...developing the correct remedy to make the series stationary is the difficult step ... In the early days of Box-Jenkins development practictioners were directed to difference to deal with these symptoms. Modern-day approaches also consider deterministic components such as Pulse,Step, Seasonal Pulse and/or Local Time Trends as identified via INTERVENTION DETECTION . I suggest that you search DOWNLOAD.COM or TUCOWS.COM for a FREEWARE program called FreeFore which automatically tests for and remedies for all the requirements underlying the model including all that I have mentioned in this post. regards Dave R Automatic Forecasting Systems 215-675-0652 P.S. If I can help privately please call or let me know when you can call ... > > thanks. . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
