A Continuous-Time Semi-Markov System Governed by Stepwise Transitions

Vlad Stefan Barbu, Guglielmo D’Amico and Andreas Makrides
Additional contact information
Vlad Stefan Barbu: Laboratory of Mathematics Raphaël Salem, University of Rouen-Normandy, UMR 6085, Avenue de l’Université, BP.12, F-76801 Saint-Étienne-du-Rouvray, France
Guglielmo D’Amico: Department of Economics, University “G. d’Annunzio” of Chieti-Pescara, Viale Pindaro 42, 65127 Pescara, Italy
Andreas Makrides: Department of Statistics and Actuarial-Financial Mathematics, University of the Aegean, GR-83200 Samos, Greece

Mathematics, 2022, vol. 10, issue 15, 1-12

Abstract: In this paper, we introduce a class of stochastic processes in continuous time, called step semi-Markov processes. The main idea comes from bringing an additional insight to a classical semi-Markov process: the transition between two states is accomplished through two or several steps. This is an extension of a previous work on discrete-time step semi-Markov processes. After defining the models and the main characteristics of interest, we derive the recursive evolution equations for two-step semi-Markov processes.

Keywords: continuous-time semi-Markov processes; step semi-Markov processes; minimum class of distributions; stochastic modelling (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-7390/10/15/2745/pdf (application/pdf)
https://www.mdpi.com/2227-7390/10/15/2745/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jmathe:v:10:y:2022:i:15:p:2745-:d:879207

Access Statistics for this article

Mathematics is currently edited by Ms. Emma He

More articles in Mathematics from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().