Wavelet-based simulation of random processes from certain classes with given accuracy and reliability

Turchyn Ievgen ()
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Turchyn Ievgen: Mechanics and Mathematics Department, Oles Honchar Dnipro National University, 72, Gagarin Av., Dnipro, 49010, Ukraine

Monte Carlo Methods and Applications, 2019, vol. 25, issue 3, 217-225

Abstract: We consider stochastic processes Y⁢(t){Y(t)} which can be represented as Y⁢(t)=(X⁢(t))s{Y(t)=(X(t))^{s}}, s∈ℕ{s\in\mathbb{N}}, where X⁢(t){X(t)} is a stationary strictly sub-Gaussian process, and build a wavelet-based model that simulates Y⁢(t){Y(t)} with given accuracy and reliability in Lp⁢([0,T]){L_{p}([0,T])}. A model for simulation with given accuracy and reliability in Lp⁢([0,T]){L_{p}([0,T])} is also built for processes Z⁢(t){Z(t)} which can be represented as Z⁢(t)=X1⁢(t)⁢X2⁢(t){Z(t)=X_{1}(t)X_{2}(t)}, where X1⁢(t){X_{1}(t)} and X2⁢(t){X_{2}(t)} are independent stationary strictly sub-Gaussian processes.

Keywords: Wavelets; sub-Gaussian random processes; simulation (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1515/mcma-2019-2042

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