I must be missing something, Roger. It seems to me that your program would flag a bunch of locations where there had, at some time in the past, been high levels of activity. I'll call them swarms (for convenience' sale), though, due to the size of the squares, and without knowledge of what time-span is involved in accumulating over 200 events, that word is undoubtedly inaccurate. These 5-degree squares would include areas of after-shock activity, normally high seismicity, and so on. So, you now have a collection of places where "swarms" once occurred. I would expect that considerably more than half of all swarms that have occurred have since stopped. No?

While writing the above, it occurred to me that such an output as you've produced is, in a way, fractal. That occurred to me because my first, rapid reading (combined with Todd's response still floating around in one of my lobes) left me thinking we were talking microquakes, and I also was thinking tiny lat/long squares. But my mistake might be instructive. I had composed half of my response above before I re-read and found we were talking M5 and above, and very large lat/long squares. But the principles involved should be independent of scale. If you think of it in terms of, say, California, small lat/long squares, and microquakes, then, to me, at least, the strangeness of your result disappears.

Also - again, I may be missing something, but - wouldn't you expect that around half of all events in a sequence to be overdue in the sense that, if you compute the average time between events, then, by definition, about half of the intervals will exceed that length? Your program immediately flags sequences the moment that interval is exceeded (by a microsecond?). The fact that over half of them are flagged might be because your program actually involves, necessarily, more than a microsecond lapse . . .

Michael F. Williams
Arroyo Grande, CA USA