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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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| Autori principali: | , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Genetics Society of America
2009
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| Soggetti: | |
| Accesso online: | 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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