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A Generalized, Likelihood-Free Method for Posterior Estimation

Recent advancements in Bayesian modeling have allowed for likelihood-free posterior estimation. Such estimation techniques are crucial to the understanding of simulation-based models, whose likelihood functions may be difficult or even impossible to derive. However, current approaches are limited by...

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Hlavní autoři: Turner, Brandon M., Sederberg, Per B.
Médium: Artigo
Jazyk:Inglês
Vydáno: 2014
Témata:
On-line přístup:https://ncbi.nlm.nih.gov/pmc/articles/PMC4143986/
https://ncbi.nlm.nih.gov/pubmed/24258272
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3758/s13423-013-0530-0
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