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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Vydané v:	IEEE/SICE/RSJ International Conference on Multisensor Fusion and Integration for Intelligent Systems s. 1 - 8
Hlavní autori:	Rosato, Conor, Varsi, Alessandro, Murphy, Joshua, Maskell, Simon
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 27.11.2023
Predmet:	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
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