On one way of modeling a stochastic process with given accuracy and reliability

Ianevych Tetiana (), Rozora Iryna () and Pashko Anatolii ()
Additional contact information
Ianevych Tetiana: Department of Probability Theory, Statistics and Actuarial Mathematics, Faculty of Mechanics and Mathematics, Taras Shevchenko National University of Kyiv, 60 Volodymyrska str., 01601 Kyiv, Ukraine
Rozora Iryna: Department of Applied Statistics, Faculty of Computer Science and Cybernetics, Taras Shevchenko National University of Kyiv, 60 Volodymyrska str., 01601 Kyiv, Ukraine
Pashko Anatolii: Department of Theoretical Cybernetics, Faculty of Computer Science and Cybernetics, Taras Shevchenko National University of Kyiv, 60 Volodymyrska str., 01601 Kyiv, Ukraine

Monte Carlo Methods and Applications, 2022, vol. 28, issue 2, 135-147

Abstract: The paper is devoted to one possible way of the model construction for the stationary Gaussian process with given accuracy and reliability in functional space C ⁢ ( [ 0 , T ] ) {C([0,T])} .

Keywords: Simulation; Gaussian process; Accuracy and Reliability; stationary process (search for similar items in EconPapers)
Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1515/mcma-2022-2110 (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:28:y:2022:i:2:p:135-147:n:3

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

DOI: 10.1515/mcma-2022-2110

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 ().