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arXiv · 1812.10939

Particle-based adaptive-lag online marginal smoothing in general state-space models

Johan Alenlöv·Jimmy Olsson
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Abstract

We present a novel algorithm, an adaptive-lag smoother, approximating efficiently, in an online fashion, sequences of expectations under the marginal smoothing distributions in general state-space models. The algorithm evolves recursively a bank of estimators, one for each marginal, in resemblance with the so-called particle-based, rapid incremental smoother (PaRIS). Each estimator is propagated until a stopping criterion, measuring the fluctuations of the estimates, is met. The presented algorithm is furnished with theoretical results describing its asymptotic limit and memory usage.

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Johan Alenlöv, Jimmy Olsson. 2018-12-28. Particle-based adaptive-lag online marginal smoothing in general state-space models. https://doi.org/10.1109/tsp.2019.2941066

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