I'm confused here. Don't you mean that it *is* true? And in the last sentence, do you not mean that it would *not* give us further information?pic.twitter.com/sDuWvleKAR
Enough people asked for details that I wrote something about Bayesian iterated mark-and-recapture here: http://www.awebb.info/blog/iterated_mark ….https://twitter.com/AndrewM_Webb/status/1212673397106388992 …
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Ahh, sorry, I didn't realise how ambiguous the writing was there. When I said "This is clearly not true in the animation", I meant that the assumption was not true, and therefore that the total number captured *does* depend on total pop. size. I've reworded that point. Thanks!
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There is an absolutely brilliant (but sadly paywalled) 45-year-old book that includes a chapter on population size estimation and loads of other good ideas for modern data science:https://www.springer.com/gp/book/9780387728056 …
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Pls Do not check on
#libgen for this book!
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I wonderful post! I note, however, a weak point of the model: it breaks down as the animals that get trapped a lot start to like the person who does the marking, look forward to the visits, and seek them out
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We actually have a name for this phenomena in wildlife biology: trap happy.
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I used to do a lab in my biostats class like this! https://shapbio.me/courses/biolB215s19/capture_recapture.html …
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"I'm by no means an expert in frequestist statistical methods, so I don't know what the approach would be in this iterated capture case, but I gather it's complicated" Unless I'm misunderstanding, it's quite simple. You include the number of capture occasions in the likelihood.
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"The total number of animals captured in a given capture event does not depend on the total population size" In reality, it does, and the total number captured, n, is a statistic used in the multinomial capture model that accounts for this. E[n] = Np
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