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2021 Simple conditions for convergence of sequential Monte Carlo genealogies with applications
Suzie Brown, Paul A. Jenkins, Adam M. Johansen, Jere Koskela
Electron. J. Probab. 26: 1-22 (2021). DOI: 10.1214/20-EJP561


We present simple conditions under which the limiting genealogical process associated with a class of interacting particle systems with non-neutral selection mechanisms, as the number of particles grows, is a time-rescaled Kingman coalescent. Sequential Monte Carlo algorithms are popular methods for approximating integrals in problems such as non-linear filtering and smoothing which employ this type of particle system. Their performance depends strongly on the properties of the induced genealogical process. We verify the conditions of our main result for standard sequential Monte Carlo algorithms with a broad class of low-variance resampling schemes, as well as for conditional sequential Monte Carlo with multinomial resampling.


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Suzie Brown. Paul A. Jenkins. Adam M. Johansen. Jere Koskela. "Simple conditions for convergence of sequential Monte Carlo genealogies with applications." Electron. J. Probab. 26 1 - 22, 2021.


Received: 13 July 2020; Accepted: 18 November 2020; Published: 2021
First available in Project Euclid: 5 January 2021

Digital Object Identifier: 10.1214/20-EJP561

Primary: 60J90, 60J95, 65C05, 65C35


Vol.26 • 2021
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