English

Wavelet series representation for multifractional multistable Riemann-Liouville process

Probability 2020-04-14 v1

Abstract

The main goal of this paper is to construct a wavelet-type random series representation for a random field XX, defined by a multistable stochastic integral, which generates a multifractional multistable Riemann-Liouville (mmRL) process YY. Such a representation provides, among other things, an efficient method of simulation of paths of YY. In order to obtain it, we expand in the Haar basis the integrand associated with XX and we use some fundamental properties of multistable stochastic integrals. Then, thanks to the Abel's summation rule and the Doob's maximal inequality for discrete submartingales, we show that this wavelet-type random series representation of XX is convergent in a strong sense: almost surely in some spaces of continuous functions. Also, we determine an estimate of its almost sure rate of convergence in these spaces.

Keywords

Cite

@article{arxiv.2004.05874,
  title  = {Wavelet series representation for multifractional multistable Riemann-Liouville process},
  author = {Antoine Ayache and Julien Hamonier},
  journal= {arXiv preprint arXiv:2004.05874},
  year   = {2020}
}
R2 v1 2026-06-23T14:49:11.638Z