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I am looking for intermittent demand time series, i.e., demands that have "many" zeros. Such series commonly occur in the retail business for single SKUs in single locations, or as the demand for spare parts. For example:

intermittent demand example

So far, I have only found two time series in the tsintermittent package for R (one of them plotted above), but I'd really like to have many, many series to do some serious testing. (For instance, the M3 competition had 3003 time series.) Rob Hyndman's Time Series Data Library hangs on me, but there are no retail time series there, either, and there likely is nothing under "Industry".

Can anyone point me to a good source?

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    Incidentally, it seems like a time-series tag would make sense, but I don't have the rep yet to create a new tag. There are about six questions that could usefully be tagged time-series. – S. Kolassa - Reinstate Monica Jan 15 '15 at 19:40
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    If the time-series is sparse, the data may be distributed as an event list (one record per occurance, with the time of when it happened), rather than as a time series. – Joe Jan 16 '15 at 18:42
  • I think the search terms you are looking for are "burst", "anomaly" or "outlier" detection. The many zeros you mention could just be the difference from the mean. – philshem Jan 17 '15 at 15:50
  • I added the 'time-series' tag to this question and the others you linked. Thanks for bringing it up! – philshem Jan 17 '15 at 15:52
  • Would synthetic data be acceptable, or do you specifically want real, historical examples? In the real world, I've seen this type of series looking at a single business's job postings over time, but I'm afraid I don't know of any public postings data off the top of my head. – J. Miller Feb 6 '15 at 21:55

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