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A factor of 40 speed improvement . . . that’s not something that happens every day!

Charles Margossian and Ben Bales helped out with the Stan model for coronavirus from Riou et al. Riou reports:

You guys are amazing. We implemented your tricks and it reduced computation time from 3.5 days to … 2 hours (40 times less). This is way beyond what I expected, thank you so much!


  1. Dave says:

    That’s great. Would someone be able to share the nature of the advice so the rest of us can learn?

  2. Ron Wilson says:

    40 times less is negative 136.5 days. Now that’s impressive!

  3. Zhou Fang says:

    Incidentally, Andrew, in the context of “all maps of parameter estimates are misleading”, do you have any words of advice for people trying to map coronavirus?

    • Phil says:

      So far I’ve seen maps of case counts, which don’t have the artifacts that paper is concerned with. Things get misleading when you start mapping things like “cases per 100,000 population” or “transmission risk”.

      Of course, there are plenty of other ways the case counts are misleading too, perhaps the biggest of which is that all that can be mapped is _known_ cases (obviously), and I would guess the relationship between known cases and actual virus carriers is both highly variable and very uncertain (and surely varies with population density).

      In short, the case count maps may not be telling us what we really want to know, indeed probably aren’t. but they are not subject to the artifacts that parameter estimates derived from them would be.

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