I am attempting to help a friend analyze interrupted time series data, and am hoping someone on the list might have advice about how to proceed. The data, which are police reports of hate crimes over a three year period, seem less than ideal. The series is organized into weekly frequency data (a total of 156 data points). Approximately 35 of the weeks had some sort of hate crime incident (and one week had as many as 75), but the remaining points are all 0 (i.e., there were no hate crimes that week). First, I am wondering about the amount of variability required to reliably identify an ARIMA model for the series. In trying to model the series, I was amazed (and a bit frightened) by how easily all the variability was captured by either one autoregressive or one moving average term. In playing with fake data, it is clear it is possible to produce autocorrelations for any series that is not a constant, even if it has almost no variation. I�m wondering if there are any assumptions (or rules of thumb) about how much variation is necessary to use ARIMA. Second, the weeks with hate crimes are not distributed evenly over time, so the mean and standard deviation of the series are not stable. However, the series does not appear to need to be differenced, maybe because although both the mean and the standard deviation increase considerably over time, most data points are still 0. How much of a problem is this lack of stability of the mean and standard deviation? Is there a diagnostic I should be using to test homogeneity? It might be easiest for people to reply directly to me at [EMAIL PROTECTED] and I will post a summary of helpful rules of thumb/diagnostics. Thank you in advance for any advice/feedback! Barbara Lehman Claremont Graduate University =========================================================================== This list is open to everyone. Occasionally, less thoughtful people send inappropriate messages. Please DO NOT COMPLAIN TO THE POSTMASTER about these messages because the postmaster has no way of controlling them, and excessive complaints will result in termination of the list. For information about this list, including information about the problem of inappropriate messages and information about how to unsubscribe, please see the web page at http://jse.stat.ncsu.edu/ ===========================================================================
