Estimation of steady-state quantities of an HMM with some rarely generated emissions

Zakrad Az-eddine () and Nasroallah Abdelaziz ()
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Zakrad Az-eddine: Mathematics Department, Semlalia Faculty of Sciences, Cadi Ayyad University, B.P. 2390, Marrakech, Morocco
Nasroallah Abdelaziz: Mathematics Department, Semlalia Faculty of Sciences, Cadi Ayyad University, B.P. 2390, Marrakech, Morocco

Monte Carlo Methods and Applications, 2022, vol. 28, issue 1, 27-44

Abstract: We propose to apply the importance sampling and the antithetic variates statistical techniques to estimate steady-state quantities of an Hidden Markov chain (HMM) of which certain emissions are rarely generated. Compared to standard Monte Carlo simulation, the use of these techniques, allow a significant reduction in simulation time. Numerical Monte Carlo examples are studied to show the usefulness and efficiency of the proposed approach.

Keywords: Hidden Markov chain; Monte Carlo simulation; steady-state; variance reduction; importance sampling; antithetic variates (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1515/mcma-2022-2103

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