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Kéry and Schaub’s Bayesian Population Analysis Translated to Stan

Hiroki ITÔ has done everyone a service in translating to Stan the example models [update: only chapters 3–9 so far, not the whole book; the rest are in the works] from

You can find the code in our example-models repository on GitHub:

This greatly expands on the ecological models we previously had available and should make a great jumping-off point for people looking to fit models for ecology. Hiroki did a fantastic job translating everything, and as an added bonus, he included the data and the R code to fit the models as part of the repository.

If anyone else has books they’d like to translate and publish as part of our example models suite, let us know. We’re more than happy to help with the modeling issues and provide feedback.

P.S. Ecologists have the best images! Probably because nature’s a big part of their job—Hiroki ITÔ is a forestry researcher.


  1. Jeremy Fox says:

    Off topic, but re: ecologists having the best images, yes, we’re spoiled in that many of us work in attractive outdoor settings. Indeed, we’re spoiled to the point where I’ve become kind of bored with conventional pretty pictures of ecologists doing field work. I find myself yearning for more creative images that still convey something of what ecologists (and other scientists) do:

  2. jrkrideau says:

    That does not look like a cat to me!

  3. Dalton says:

    This is so great. I have well thumbed copy of Kery and Schaub. Now what would be truly awesome would be an rstanarm like package that combines something like the syntax of Jeff Laake’s marked package with the power of Stan. I think that’s probably some tricky coding, but that’s something I’d love to help out with.

  4. Jonah says:

    Dalton, I haven’t looked closely at these models yet, but if you’d like to work on contributing this (or some of this) functionality to rstanarm then definitely let us know! Ben and I can help get you familiar with the internals of rstanarm and help with any other challenges along the way.

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