An approximate formula for calculating the expectations of functionals from random processes based on using the Wiener chaos expansion

Egorov Alexander ()
Additional contact information
Egorov Alexander: Institute of Mathematics, National Academy of Sciences of Belarus, Surganova str., 10, Minsk, Belarus

Monte Carlo Methods and Applications, 2020, vol. 26, issue 4, 285-292

Abstract: In this work, we propose a new method for calculating the mathematical expectation of nonlinear functionals from random processes. The method is based on using Wiener chaos expansion and approximate formulas, exact for functional polynomials of given degree. Examples illustrating approximation accuracy are considered.

Keywords: Functionals of random processes; Wiener chaos expansion; mathematical expectations of functionals; approximate formulas (search for similar items in EconPapers)
Date: 2020
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/mcma-2020-2074 (text/html)
For access to full text, subscription to the journal or payment for the individual article is required.

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:bpj:mcmeap:v:26:y:2020:i:4:p:285-292:n:4

Ordering information: This journal article can be ordered from
https://www.degruyter.com/journal/key/mcma/html

DOI: 10.1515/mcma-2020-2074

Access Statistics for this article

Monte Carlo Methods and Applications is currently edited by Karl K. Sabelfeld

More articles in Monte Carlo Methods and Applications from De Gruyter
Bibliographic data for series maintained by Peter Golla ().