On the approximations of solutions to stochastic differential delay equations with Poisson random measure via Taylor series
Author(s) -
Marija Milošević
Publication year - 2013
Publication title -
filomat
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.449
H-Index - 34
eISSN - 2406-0933
pISSN - 0354-5180
DOI - 10.2298/fil1301201m
Subject(s) - mathematics , taylor series , mathematical analysis , stochastic differential equation , poisson distribution , series (stratigraphy) , differential equation , compound poisson process , measure (data warehouse) , jump process , stochastic partial differential equation , jump , poisson process , paleontology , statistics , physics , quantum mechanics , database , computer science , biology
The subject of this paper is the analytic approximation of solution to stochastic differential delay equations with Poisson jump. We introduce approximate methods for stochastic differential equations driven by Poisson random measure, as well as for those driven by Poisson process. In both cases, approx- imate equations are defined on equidistant partitions of the time interval, and their coefficients are Taylor approximations of the coefficients of the initial equation. It will be shown that the approximate solutions converge in theL p -sense and almost surely to the solutions of the corresponding initial equations. The order of the L p -convergence of the approximate solutions to the solution of the initial equation is established and it increases when the number of degrees in Taylor approximations of coefficients increases.
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