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A general framework for simulation of fractional fields
- Source :
- Stochastic Processes and their Applications, Stochastic Processes and their Applications, Elsevier, 2008, 118 (9), pp.1489--1517, Stochastic Processes and their Applications, 2008, 118 (9), pp.1489--1517
- Publication Year :
- 2008
- Publisher :
- Elsevier BV, 2008.
-
Abstract
- International audience; Besides fractional Brownian motion most non-Gaussian fractional fields are obtained by integration of deterministic kernels with respect to a random infinitely divisible measure. In this paper, generalized shot noise series are used to obtain approximations of most of these fractional fields, including linear and harmonizable fractional stable fields. Almost sure and $L^r$-norm rates of convergence, relying on asymptotic developments of the deterministic kernels, are presented as a consequence of an approximation result concerning series of symmetric random variables. When the control measure is infinite, normal approximation has to be used as a complement. The general framework is illustrated by simulations of classical fractional fields.
- Subjects :
- Statistics and Probability
Fractional Brownian motion
Random field
Series (mathematics)
Stochastic process
Applied Mathematics
010102 general mathematics
Mathematical analysis
01 natural sciences
Measure (mathematics)
Fractional fields
Fractional calculus
[MATH.MATH-PR]Mathematics [math]/Probability [math.PR]
010104 statistics & probability
Random measure
Convergence of random variables
Modeling and Simulation
Modelling and Simulation
Infinitely divisible distributions
0101 mathematics
Simulation of random fields
Mathematics
Subjects
Details
- ISSN :
- 03044149 and 1879209X
- Volume :
- 118
- Issue :
- 9
- Database :
- OpenAIRE
- Journal :
- Stochastic Processes and their Applications
- Accession number :
- edsair.doi.dedup.....f2734ae6b8c2d1bd6074335fc14bac16
- Full Text :
- https://doi.org/10.1016/j.spa.2007.09.008