The dynamics of UFO sightings

The Economist reports on UFO sightings:

UFOdataThis deserves a model:

UFOs

UFOs.vpm (Vensim published model, requires Pro/DSS or the free Reader)

The model is a mixed discrete/continuous simulation of an individual sleeping, working and drinking. This started out as a multi-agent model, but I realized along the way that sleeping, working and drinking is a fairly ergodic process on long time scales (at least with respect to UFOs), so one individual with a distribution of behaviors over time or simulations is as good as a population of agents.

The model replicates the data somewhat faithfully:

UFOdistributionThe model shows a morning peak (people awake but out and about) and a workday dip (inside, lurking near the water cooler) but the data do not. This suggests to me that:

  • Alcohol is the dominant factor in sightings.
  • I don’t party nearly enough to see a UFO.

Actually, now that I’ve built this version, I think the interesting model would have a longer time horizon, to address the non-ergodic part: contagion of sightings across individuals.

h/t Andreas Größler.

2 thoughts on “The dynamics of UFO sightings”

  1. Which goes to prove that a: UFO’s can detect alcohol on your breath from light years away and home in on same and b: If you are sober and out of alcohol and see a UFO it’s good news because a: someone near you has alcohol and b: seeing a UFO together is proven to be a strong predictor of people sharing alcohol enthusiastically.

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