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Daniel Wegmann

Researcher at University of Fribourg

Publications -  80
Citations -  5342

Daniel Wegmann is an academic researcher from University of Fribourg. The author has contributed to research in topics: Population & Approximate Bayesian computation. The author has an hindex of 31, co-authored 72 publications receiving 4703 citations. Previous affiliations of Daniel Wegmann include University of California, Los Angeles & Swiss Institute of Bioinformatics.

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Efficient Approximate Bayesian Computation Coupled With Markov Chain Monte Carlo Without Likelihood

TL;DR: The principal idea is to relax the tolerance within MCMC to permit good mixing, but retain a good approximation to the posterior by a combination of subsampling the output and regression adjustment, which will realize substantial computational advances over standard ABC.
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Early farmers from across Europe directly descended from Neolithic Aegeans

TL;DR: This study demonstrates a direct genetic link between Mediterranean and Central European early farmers and those of Greece and Anatolia, extending the European Neolithic migratory chain all the way back to southwestern Asia.
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ABCtoolbox: a versatile toolkit for approximate Bayesian computations

TL;DR: ABCtoolbox allows a user to perform all the necessary steps of a full ABC analysis, from parameter sampling from prior distributions, data simulations, computation of summary statistics, estimation of posterior distributions, model choice, validation of the estimation procedure, and visualization of the results.