Alive SMC(2) : Bayesian model selection for low-count time series models with intractable likelihoods

In this article we present a new method for performing Bayesian parameter inference and model choice for low- count time series models with intractable likelihoods. The method involves incorporating an alive particle filter within a sequential Monte Carlo (SMC) algorithm to create a novel exact-appr...

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Veröffentlicht in:	Biometrics 2016-06, Vol.72 (2), p.344-353
Hauptverfasser:	Drovandi, Christopher C, McCutchan, Roy A
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Animals Bayes Theorem Computer Simulation Humans Iatrogenic Disease Markov Chains Models, Biological Models, Statistical Monte Carlo Method Prion Diseases Time Factors
Online-Zugang:	Volltext
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