An O(log2 N) SMC2 Algorithm on Distributed Memory with an Approx. Optimal L-Kernel

Calibrating statistical models using Bayesian inference often requires both accurate and timely estimates of parameters of interest. Particle Markov Chain Monte Carlo (p-MCMC) and Sequential Monte Carlo Squared (SMC 2 ) are two methods that use an unbiased estimate of the log-likelihood obtained fro...

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Veröffentlicht in:	IEEE/SICE/RSJ International Conference on Multisensor Fusion and Integration for Intelligent Systems S. 1 - 8
Hauptverfasser:	Rosato, Conor, Varsi, Alessandro, Murphy, Joshua, Maskell, Simon
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 27.11.2023
Schlagworte:	Bayes methods Bayesian inference biomedical applications distributed memory Markov processes Monte Carlo methods parallel algorithms Parameter estimation Particle filters particle Markov Chain Monte Carlo Program processors Recycling SMC 2
ISSN:	2767-9357
Online-Zugang:	Volltext
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