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

Approximate Bayesian computation (ABC) techniques permit inferences in complex demographic models, but are computationally inefficient. A Markov chain Monte Carlo (MCMC) approach has been proposed (Marjoram et al. 2003), but it suffers from computational problems and poor mixing. We propose several...

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Hlavní autoři: Wegmann, Daniel, Leuenberger, Christoph, Excoffier, Laurent
Médium: Artigo
Jazyk:Inglês
Vydáno: Genetics Society of America 2009
Témata:
On-line přístup:https://ncbi.nlm.nih.gov/pmc/articles/PMC2728860/
https://ncbi.nlm.nih.gov/pubmed/19506307
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1534/genetics.109.102509
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