Maximally Distributed Random Fields under Sublinear Expectation

Xinpeng Li () and Shige Peng ()
Additional contact information
Xinpeng Li: Shandong University, Research Center for Mathematics and Interdisciplinary Sciences
Shige Peng: Shandong University, School of Mathematics

A chapter in Stochastic Analysis, Filtering, and Stochastic Optimization, 2022, pp 339-356 from Springer

Abstract: Abstract This paper focuses on the maximal distribution on sublinear expectation space and introduces a new type of random fields with the maximally distributed finite-dimensional distribution. The corresponding spatial maximally distributed white noise is constructed, which includes the temporal-spatial situation as a special case due to the symmetrical independence property of maximal distribution. In addition, the stochastic integrals with respect to the spatial or temporal-spatial maximally distributed white noises are established in a quite direct way without the usual assumption of adaptability for integrand.

Date: 2022
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:spr:sprchp:978-3-030-98519-6_14

Ordering information: This item can be ordered from
http://www.springer.com/9783030985196

DOI: 10.1007/978-3-030-98519-6_14

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().