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Time changes that result in multiple points in continuous-time Markov counting processes

  • Bretó, Carles
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    We show that randomly changing time of simple, infinitesimally equi-dispersed, non-linear birth–death processes can result in compound, infinitesimally over-dispersed processes. We provide sufficient and necessary conditions and illustrate this with various time changes and examples from scientific and engineering fields.

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    File URL: http://www.sciencedirect.com/science/article/pii/S016771521200301X
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    Article provided by Elsevier in its journal Statistics & Probability Letters.

    Volume (Year): 82 (2012)
    Issue (Month): 12 ()
    Pages: 2229-2234

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    Handle: RePEc:eee:stapro:v:82:y:2012:i:12:p:2229-2234
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    1. Kumar, A. & Nane, Erkan & Vellaisamy, P., 2011. "Time-changed Poisson processes," Statistics & Probability Letters, Elsevier, vol. 81(12), pages 1899-1910.
    2. Carles Bretó & Edward L. Ionides, 2011. "Compound Markov counting processes and their applications to modeling infinitesimally over-dispersed systems," Statistics and Econometrics Working Papers ws111914, Universidad Carlos III, Departamento de Estadística y Econometría.
    3. Hélyette Geman & Dilip B. Madan & Marc Yor, 2001. "Time Changes for Lévy Processes," Mathematical Finance, Wiley Blackwell, vol. 11(1), pages 79-96.
    4. M. J. Faddy & J. S. Fenlon, 1999. "Stochastic modelling of the invasion process of nematodes in fly larvae," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 48(1), pages 31-37.
    5. Bretó, Carles & Ionides, Edward L., 2011. "Compound Markov counting processes and their applications to modeling infinitesimally over-dispersed systems," Stochastic Processes and their Applications, Elsevier, vol. 121(11), pages 2571-2591, November.
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