10-07-2012 04:58 PM
I have a data set of time series observations with a seasonal trend.
I have de-trended and de-seasonalized it using by first differencing and also taking the log of observations. However, when I want to fit an ARIMA model, It is almost impossible to have a proper fit.
This is my code and I have attached the data set.
proc import datafile="liquor.csv"
data liquor (rename=(var1=sales));
t = _n_ ;
*The log transformation is predeferencing transformation to make constant seasonal variation;
*These are three different differencing transformation to make the data stationary;
proc timeseries data=liquor
id date interval=month accumulate=avg;
proc arima data=LIQUOR ;
identify var=x esacf ;
estimate p=2 q=3;
Any suggestions and help is greatly appreciated.
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