Inference and rare event simulation for stopped Markov processes via reverse-time sequential Monte Carlo

DOI10.1007/s11222-017-9722-1zbMath1505.62232arXiv1603.02834OpenAlexW3101522605MaRDI QIDQ1702290

Dario Spanò, Jere Koskela, Paul A. Jenkins

Publication date: 28 February 2018

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1603.02834

zbMATH Keywords

time reversalsequential Monte Carlointractable likelihoodrare event simulationstopped Markov process

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Computational methods for problems pertaining to statistics (62-08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Markov processes: estimation; hidden Markov models (62M05) Monte Carlo methods (65C05) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Genetics and epigenetics (92D10)

Related Items (2)

Asymptotic behaviour of sampling and transition probabilities in coalescent models under selection and parent dependent mutations ⋮ A dual process for the coupled Wright-Fisher diffusion

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