Moments and polynomial expansions in discrete matrix-analytic models

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Calculation of factorial moments and point probabilities is considered in integer-valued matrix-analytic models at a finite horizon T. Two main settings are considered, maxima of integer-valued downward skipfree Lévy processes and Markovian point process with batch arrivals (BMAPs). For the moments of the finite-time maxima, the procedure is to approximate the time horizon T by an Erlang distributed one and solve the corresponding matrix Wiener–Hopf factorization problem. For the BMAP, a structural matrix-exponential representation of the factorial moments of N(T) is derived. Moments are then used as a computational vehicle to provide a converging Gram–Charlier series for the point probabilities. Topics such as change-of-measure techniques and time inhomogeneity are also discussed.

Original languageEnglish
JournalStochastic Processes and Their Applications
Volume150
Pages (from-to)1165-1188
ISSN0304-4149
DOIs
Publication statusPublished - 2022

Bibliographical note

Publisher Copyright:
© 2021 Elsevier B.V.

    Research areas

  • BMAP, Erlangization, Factorial moments, Matrix exponentials, Richardson extrapolation, Wiener–Hopf factorization

ID: 289461005