 A general approach to sample path generation of infinitely divisible processes via shot noise representationReiichiro Kawai Statistics & Probability Letters, 2021, vol. 174, issue C Abstract: We establish a sample path generation scheme in a unified manner for general multivariate infinitely divisible processes based on shot noise representation of their integrators. The approximation is derived from the decomposition of the infinitely divisible process to three independent components based on jump sizes and timings: the large jumps over a compact time interval, small jumps over the entire time interval and large jumps over an unbounded time interval. The first component is taken as the approximation and is much simpler than simulation of general Gaussian processes, while the latter two components are analyzed as the error. We derive technical conditions for the two error terms to vanish in the limit and for the scaled component on small jumps to converge to a Gaussian process so as to enhance the accuracy of the weak approximation. We provide an extensive collection of examples to highlight the wide practicality of the proposed approach. Keywords: Infinitely divisible laws; Lévy processes; Fractional Lévy motions; Shot noise representation; Infinitely divisible processes (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:stapro:v:174:y:2021:i:c:s0167715221000535 Ordering information: This journal article can be ordered from DOI: 10.1016/j.spl.2021.109091 Access Statistics for this article Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul More articles in Statistics & Probability Letters from Elsevier |
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