Simulation of Gaussian stationary Ornstein–Uhlenbeck process with given reliability and accuracy in space C⁢([0,T])C([0,T])

Kozachenko Yuriy () and Petranova Marina ()
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Kozachenko Yuriy: Department of Probability Theory, Statistics and Actuarial Mathematics, Taras Shevchenko National University of Kyiv, Akademika Glushkova Avenue, Building 4-e, 03127Kyiv; and Department of Probability Theory and Mathematical Statistics, Faculty of Mathematics and Information Technology, Vasyl’ Stus Donetsk National University, 600-Richya Str. 21, 21021 Vinnytsia, Ukraine
Petranova Marina: Department of Probability Theory and Mathematical Statistics, Faculty of Mathematics and Information Technology, Vasyl’ Stus Donetsk National University, 600-Richya Str. 21, 21021Vinnytsia, Ukraine

Monte Carlo Methods and Applications, 2017, vol. 23, issue 4, 277-286

Abstract: In this paper, we construct models that approximate the Gaussian stationary Ornstein–Uhlenbeck process with given reliability 1-δ{1-\delta}, 0 0{\beta>0} in the space C⁢([0,T]){C([0,T])}.

Keywords: Gaussian process; model of process; simulation; reliability; accuracy (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:bpj:mcmeap:v:23:y:2017:i:4:p:277-286:n:2

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DOI: 10.1515/mcma-2017-0115

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