Implementing Markovian models for extendible Marshall–Olkin distributions

نویسندگان

چکیده

Abstract We derive a novel stochastic representation of exchangeable Marshall–Olkin distributions based on their death-counting processes. show that these processes are Markov. Furthermore, we provide numerically stable approximation infinitesimal generator matrices in the extendible case. This approach uses integral representations Bernstein functions to calculate generator’s first row, and then recursion remaining rows. Combining Markov with corresponding generators allows us sample flexible simulation algorithm derived from known sampling strategies. Finally, benchmark an implementation this Markov-based against alternative algorithms Lévy frailty model, Arnold exogenous shock model.

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ژورنال

عنوان ژورنال: Dependence Modeling

سال: 2022

ISSN: ['2300-2298']

DOI: https://doi.org/10.1515/demo-2022-0151