Data from: Approximate Bayesian computation for modular inference problems with many parameters: the example of migration rates

Simon Aeschbacher, Andreas Futschik & Mark A. Beaumont
We propose a two-step procedure for estimating multiple migration rates in an approximate Bayesian computation (ABC) framework, accounting for global nuisance parameters. The approach is not limited to migration, but generally of interest for inference problems with multiple parameters and a modular structure (e.g. independent sets of demes or loci). We condition on a known, but complex demographic model of a spatially subdivided population, motivated by the reintroduction of Alpine ibex (Capra ibex) into Switzerland....
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