8 votes
Accepted

Meaning of Moving Average Term in ARIMA

For time series, it is better to think about the $\alpha_t$ terms (supposed to be an independent mean zero series) as innovations, not errors. They are not modeling errors of measurements, but the ...
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7 votes

How to handle many time series?

If the 1200 products are closely related, so that trend (if any) and noise are likely to be correlated across products, a single model might make sense. If they are loosely related (so that they might ...
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5 votes

How to handle many time series?

This problem is a multivariate (simply when you have more than one time-dependent variables) time series for which you can use Vector Auto Regression (VAR) technique among some others. Explanation and ...
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4 votes

How to handle many time series?

The demand of 1200 product will often be related. There might be common events (Christmas, some large accident, ...) that influence all or many of the demands, substitution effects, ... or there may ...
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4 votes

Meaning of Moving Average Term in ARIMA

Kjetil's answer is very good, and the distinction between errors and innovations are important to understand. But there are also applications where measurement issues do result in MA-type errors. For ...
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2 votes
Accepted

Multiple SKU forecast for Intermittent Demand

You can consider aggregating demand by grouping some SKU's (group that makes more business sense) and by which you can have more points for a group. You can train (though data seems less) and then ...
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