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On Fractional Gaussian Random Fields Simulations

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  • Brouste, Alexandre
  • Istas, Jacques
  • Lambert-Lacroix, Sophie

Abstract

To simulate Gaussian fields poses serious numerical problems: storage and computing time. The midpoint displacement method is often used for simulating the fractional Brownian fields because it is fast. We propose an effective and fast method, valid not only for fractional Brownian fields, but for any Gaussian fields. First, our method is compared with midpoint for fractional Brownian fields. Second, the performance of our method is illustrated by simulating several Gaussian fields. The software FieldSim is an R package developed in R and C and that implements the procedures on which this paper focuses.

Suggested Citation

  • Brouste, Alexandre & Istas, Jacques & Lambert-Lacroix, Sophie, 2007. "On Fractional Gaussian Random Fields Simulations," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 23(i01).
    • Handle: RePEc:jss:jstsof:v:023:i01
    DOI: http://hdl.handle.net/10.18637/jss.v023.i01
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    References listed on IDEAS

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    1. Benassi, Albert & Cohen, Serge & Istas, Jacques, 1998. "Identifying the multifractional function of a Gaussian process," Statistics & Probability Letters, Elsevier, vol. 39(4), pages 337-345, August.
    2. Coeurjolly, Jean-Francois, 2000. "Simulation and identification of the fractional Brownian motion: a bibliographical and comparative study," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 5(i07).
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    Cited by:

    1. Hedi Kortas & Zouhaier Dhifaoui & Samir Ben Ammou, 2012. "On wavelet analysis of the nth order fractional Brownian motion," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 21(3), pages 251-277, August.
    2. repec:jss:jstsof:36:i04 is not listed on IDEAS

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