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arXiv · 2004.08565

Bayesian Parameter Identification for Jump Markov Linear Systems

Mark P. Balenzuela·Adrian G. Wills·Christopher Renton·Brett Ninness
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Abstract

This paper presents a Bayesian method for identification of jump Markov linear system parameters. A primary motivation is to provide accurate quantification of parameter uncertainty without relying on asymptotic in data-length arguments. To achieve this, the paper details a particle-Gibbs sampling approach that provides samples from the desired posterior distribution. These samples are produced by utilising a modified discrete particle filter and carefully chosen conjugate priors.

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Mark P. Balenzuela, Adrian G. Wills, Christopher Renton, Brett Ninness. 2021-02-10. Bayesian Parameter Identification for Jump Markov Linear Systems. https://arxiv.org/abs/2004.08565

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