Sequential Bayesian inference for spatio-temporal models of temperature and humidity data

•The paper develops a novel spatio-temporal model for temperature and humidity data.•The model is fit to streaming data by using a cutting-edge sequential Monte Carlo algorithm: the iterated batch importance sampling scheme.•We derive an on-line implementation of this algorithm which is more efficie...

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Bibliographic Details

Published in:	Journal of computational science Vol. 43; p. 101125
Main Authors:	Lai, Yingying, Golightly, Andrew, Boys, Richard J.
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.05.2020
Subjects:	Dynamic linear models (DLMs) Iterated batch importance sampling (IBIS) Parallel computing Sequential Monte Carlo (SMC) Dynamic linear models (DLMs) Parallel computing Iterated batch importance sampling (IBIS) Sequential Monte Carlo (SMC)
ISSN:	1877-7503, 1877-7511
Online Access:	Get full text
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