Path storage in the particle filter

Abstract

This article considers the problem of storing the paths generated by a particle filter and more generally by a sequential Monte Carlo algorithm. It provides a theoretical result bounding the expected memory cost by $T+CN\log N$ where $T$ is the time horizon, $N$ is the number of particles and $C$ is a constant, as well as an efficient algorithm to realise this. The theoretical result and the algorithm are illustrated with numerical experiments.

9 pages, 5 figures. To appear in Statistics and Computing

References in corpus (1)

• Uniform Time Average Consistency of Monte Carlo Particle Filters

Cited by in corpus (7)

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• Resampling Algorithms for High Energy Physics Simulations
• Anytime Monte Carlo