Linear Multifractional Stable Motion: wavelet estimation of H(·) and parameters

Abstract

Linear Fractional Stable Motion (LFSM) of Hurst parameter H and of stability parameter , is one of the most classical extensions of the well-known Gaussian Fractional Brownian Motion (FBM), to the setting of heavy-tailed stable distributions SamTaq,EmMa. In order to overcome some limitations of its areas of application, coming from stationarity of its increments as well as constancy over time of its self-similarity exponent, Stoev and Taqqu introduced in stoev2004stochastic an extension of LFSM, called Linear Multifractional Stable Motion (LMSM), in which the Hurst parameter becomes a function H(·) depending on the time variable t. Similarly to LFSM, the tail heaviness of the marginal distributions of LMSM is determined by ; also, under some conditions, its self-similarity is governed by H(·) and its path roughness is closely related to H(·)-1/. Namely, it was shown in stoev2004stochastic that H(t0) is the self-similarity exponent of LMSM at a time t0≠ 0; moreover, very recently, it was established in hamonier2012lmsm, that the quantities t∈ I H(t)-1/, and H(t0)-1/, are respectively the uniform H\"older exponent of LMSM on a compact interval I, and its local H\"older exponent at t0. The main goal of our article, is to construct, using wavelet coefficients of LMSM, strongly consistent (i.e. almost surely convergent) statistical estimators of t∈ I H(t), H(t0), and ; our estimation results, are obtained when ∈ (1,2), and, H(·) is a H\"older function smooth enough, with values in a compact subinterval [H,H] of (1/,1).

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