Large deviations for multidimensional state-dependent shot-noise processes

A. Budhiraja, P. Nyquist

Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

10 Citaten (Scopus)


Shot-noise processes are used in applied probability to model a variety of physical systems in, for example, teletraffic theory, insurance and risk theory, and in the engineering sciences. In this paper we prove a large deviation principle for the sample-paths of a general class of multidimensional state-dependent Poisson shot-noise processes. The result covers previously known large deviation results for one-dimensional stateindependent shot-noise processes with light tails. We use the weak convergence approach to large deviations, which reduces the proof to establishing the appropriate convergence of certain controlled versions of the original processes together with relevant results on existence and uniqueness.

Originele taal-2Engels
Pagina's (van-tot)1097-1114
Aantal pagina's18
TijdschriftJournal of Applied Probability
Nummer van het tijdschrift4
StatusGepubliceerd - 1 dec 2015
Extern gepubliceerdJa


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