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arXiv · 1812.00260

The semi-Markov beta-Stacy process: a Bayesian non-parametric prior for semi-Markov processes

Andrea Arfè·Stefano Peluso·Pietro Muliere
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Abstract

The literature on Bayesian methods for the analysis of discrete-time semi-Markov processes is sparse. In this paper, we introduce the semi-Markov beta-Stacy process, a stochastic process useful for the Bayesian non-parametric analysis of semi-Markov processes. The semi-Markov beta-Stacy process is conjugate with respect to data generated by a semi-Markov process, a property which makes it easy to obtain probabilistic forecasts. Its predictive distributions are characterized by a reinforced random walk on a system of urns.

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Andrea Arfè, Stefano Peluso, Pietro Muliere. 2018-12-01. The semi-Markov beta-Stacy process: a Bayesian non-parametric prior for semi-Markov processes. https://arxiv.org/abs/1812.00260

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