EM algorithm for stochastic hybrid systems

Masaaki Fukasawa ()
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Masaaki Fukasawa: Osaka University

Statistical Inference for Stochastic Processes, 2021, vol. 24, issue 1, No 8, 223-239

Abstract: Abstract A stochastic hybrid system, also known as a switching diffusion, is a continuous-time Markov process with state space consisting of discrete and continuous parts. We consider parametric estimation of the Q matrix for the discrete state transitions and of the drift coefficient for the diffusion part. First, we derive the likelihood function under the complete observation of a sample path in continuous-time. Then, extending a finite-dimensional filter for hidden Markov models developed by Elliott et al. (Hidden Markov Models, Springer, 1995) to stochastic hybrid systems, we derive the likelihood function and the EM algorithm under a partial observation where the continuous state is monitored continuously in time, while the discrete state is unobserved.

Keywords: Partial observation; Filtering; Stochastic hybrid system (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s11203-020-09231-3

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