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

DOI10.1515/MCMA-2022-2110zbMath1491.60052OpenAlexW4220777248MaRDI QIDQ2671519

Anatolii Pashko, Tetiana O. Ianevych, Iryna V. Rozora

Publication date: 3 June 2022

Published in: Monte Carlo Methods and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/mcma-2022-2110

zbMATH Keywords

simulationGaussian processstationary processaccuracy and reliability

Mathematics Subject Classification ID

Gaussian processes (60G15) Stationary stochastic processes (60G10) Applications of renewal theory (reliability, demand theory, etc.) (60K10)

Cites Work

• Correlation theory of stationary and related random functions. Volume II: Supplementary notes and references
• On the modeling of linear system input stochastic processes with given accuracy and reliability
• Simulation of Gaussian stationary Ornstein-Uhlenbeck process with given reliability and accuracy in space \(C([0,T)\)]
• Comparative analysis of multiscale Gaussian random field simulation algorithms
• Simulation of weakly self-similar stationary increment \(\mathbf{Sub}_\varphi(\Omega)\)-processes: A series expansion approach
• Properties of Some Random Series
• Construction of the Karhunen–Loève model for an input Gaussian process in a linear system by using the output process
• On an expansion of random processes in series
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