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Modern Stochastics: Theory and Applications*

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A multiplicative wavelet-based model for simulation of a random process
Volume 2, Issue 4 (2015), pp. 309–325
Ievgen Turchyn  

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https://doi.org/10.15559/15-MSTA33
Pub. online: 24 September 2015      Type: Research Article      Open accessOpen Access

Received
21 July 2015
Revised
8 September 2015
Accepted
11 September 2015
Published
24 September 2015

Abstract

We find a multiplicative wavelet-based representation for stochastic processes that can be represented as the exponent of a second-order centered random process. We propose a wavelet-based model for simulation of such a stochastic process and find its rates of convergence to the process in different functional spaces in terms of approximation with given accuracy and reliability. This approach allows us to simulate stochastic processes (including certain classes of processes with heavy tails) with given accuracy and reliability.

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Turchyn, I.: Haar wavelet and simulation of stochastic processes. Contemp. Math. Stat. 3, 1–7 (2015)
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Keywords
Sub-Gaussian random processes simulation

MSC2010
60G12

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