Hitting probabilities and fractal dimensions of multiparameter multifractional Brownian motion

The main goal of this paper is to study the sample path properties for the harmonisable-type N-parameter multifractional Brownian motion, whose local regularities change as time evolves. We provide the upper and lower bounds on the hitting probabilities of an （N, d）-multifractional Brownian motion. Moreover, we determine the Hausdorff dimension of its inverse images, and the Hausdorff and packing dimensions of its level sets.     

Statistical Inference with Fractional Brownian Motion

We give a test between two complex hypothesis; namely we test whether a fractional Brownian motion (fBm) has a linear trend against a certain non-linear trend. We study some related questions, like goodness-of-fit test and volatility estimation in these models.     

Statistical Multiplexing of Homogeneous Fractional Brownian Streams

In this paper, the statistical multiplexing of independent fractional Brownian traffic streams with the same Hurst value 0.5<H<1 is studied. The buffer overflow probabilities based on steady-state and transient queue length tail distributions are used respectively as the common performance criterion. Under general conditions, the minimal buffer allocation to the merged traffic is identified in either case so that strictly positive bandwidth savings are realized. Impact of the common H value on multiplexing gains is investigated. The analytical results are applicable in data network engineering problems, where ATM is deployed as the transport network carrying long-range dependent data traffic.     

Estimating the Parameters of a Fractional Brownian Motion by Discrete Variations of its Sample Paths

This paper develops a class of consistent estimators of the parameters of a fractional Brownian motion based on the asymptotic behavior of the k-th absolute moment of discrete variations of its sampled paths over a discrete grid of the interval [0,1]. We derive explicit convergence rates for these types of estimators, valid through the whole range 0 < H < 1 of the self-similarity parameter. We also establish the asymptotic normality of our estimators. The effectiveness of our procedure is investigated in a simulation study. This revised version was published online in June 2006 with corrections to the Cover Date.     

On intersections of independent anisotropic Gaussian random fields

Let XH = {XH(s),s ∈RN1} and X K = {XK(t),t ∈R N2} be two independent anisotropic Gaussian random fields with values in R d with indices H =(H1,...,HN1) ∈(0,1)N1,K =(K1,...,KN2) ∈(0,1) N2,respectively.Existence of intersections of the sample paths of X H and X K is studied.More generally,let E1■RN1,E2■RN2 and FRd be Borel sets.A necessary condition and a sufficient condition for P{(XH(E1)∩XK(E2))∩F≠Ф}>0 in terms of the Bessel-Riesz type capacity and Hausdorff measure of E1×E2×F in the metric space(RN1+N2+d,) are proved,where  is a metric defined in terms of H and K.These results are applicable to solutions of stochastic heat equations driven by space-time Gaussian noise and fractional Brownian sheets.     

Continuity in law with respect to the Hurst index of some additive functionals of sub-fractional Brownian motion

In this article, first, we prove some properties of the sub-fractional Brownian motion introduced by Bojdecki et al. [Statist. Probab. Lett. 69(2004):405–419]. Second, we prove the continuity in law, with respect to small perturbations of the Hurst index, in some anisotropic Besov spaces, of some continuous additive functionals of the sub-fractional Brownian motion. We prove that our result can be obtained easily, by using the decomposition in law of the sub-fractional Brownian motion given by Bardina and Bascompte [Collect. Math. 61(2010):191–204] and Ruiz de Chavez and Tudor [Math. Rep. 11(2009):67–74], without using the result of Wu and Xiao [Stoch. Proc. Appl. 119(2009):1823–1844] by connecting the sub-fractional Brownian motion to its stationary Gaussian process through Lamperti’s transform. This decomposition in law leads to a better understanding and simple proof of our result.     

Efficent Generation of Fractional Brownian Motion for Simulation of Infrared Focal-plane Array Calibration Drift

Infrared focal-plane arrays suffer from a type of 1/f noise which leads to slow drifts in detected radiation levels following calibration. This noise can be modeled by fractional Brownian motion (FBM), with an empirical Hurst parameter (H) in the range 0 < H < 1 / 2. For such noise we examine the statistics of both the maximum deviation from the calibration point during a fixed time, and the time to reach a fixed deviation from the calibration point. We employ analytical and numerical means; for the latter, we provide a new algorithm for generating a discrete-time version of FBM with 0 < H 1 / 2 which is fast (order N log N), and exact. Statistics of the maximum deviation show the same qualitative behavior for different values of H, and rapidly approach a limit as the length N increases. Results for first passage times, in contrast, vary markedly with H, but not with N.     

A Turning-Band Method for the Simulation of Anisotropic Fractional Brownian Fields

In this article, we propose a method for simulating realizations of two-dimensional anisotropic fractional Brownian fields (AFBF) introduced by Bonami and Estrade. The method is adapted from a generic simulation method called the turning-band method (TBM) due to Matheron. The TBM reduces the problem of simulating a field in two dimensions by combining independent processes simulated on oriented bands. In the AFBF context, the simulation fields are constructed by discretizing an integral equation arising from the application of the TBM to nonstationary anisotropic fields. This guarantees the convergence of simulations as the step of discretization is decreased. The construction is followed by a theoretical study of the convergence rate (the detailed proofs are available in the online supplementary materials). Another key feature of this work is the simulation of band processes. Using self-similarity properties, processes are simulated exactly on bands with a circulant embedding method, so that simulation errors are exclusively due to the field approximation. Moreover, we design a dynamic programming algorithm that selects band orientations achieving the optimal trade-off between computational cost and precision. Finally, we conduct a numerical study showing that the approximation error does not significantly depend on the regularity of the fields to be simulated, nor on their degree of anisotropy. Experiments also suggest that simulations preserve the statistical properties of the original field.     

Fast and exact synthesis of some operator scaling Gaussian random fields

Operator scaling Gaussian random fields, as anisotropic generalizations of self-similar fields, know an increasing interest for theoretical studies in the literature. However, up to now, they were only defined through stochastic integrals, without explicit covariance functions. In this paper we exhibit explicit covariance functions, as anisotropic generalizations of fractional Brownian fields ones, and define corresponding Operator scaling Gaussian random fields. This allows us to propose a fast and exact method of simulation in dimension 2 based on the circulant embedding matrix method, following ideas of Stein [34] for fractional Brownian surfaces syntheses. This is a first piece of work to popularize these models in anisotropic spatial data modeling.     

The Zariski problem for function fields of quadratic forms

By `a quadratic function field' is meant the affine function field of a nonsingular quadratic form of dimension . What quadratic function fields contain a given quadratic function field ? This problem is solved here for quadratic forms of dimensions 3 and 4, and an application to the Zariski cancellation problem for quadratic function fields is given.

     

带跳的分数维Brown 运动幂变差的渐近行为

本文研究了X_t = B^H_t + ξ_t 现实幂变差的渐近理论, B^H 为Hurst 指数为H∈(0,1) 的分数维Brown 运动,ξ为与B^H独立的非Gauss Lévy 过程, 我们给出了其大数定律, 以及经适当中心化的中 心极限定理, 这些结果将为处理具有长期记忆跳过程的统计问题提供理论基础.     

Berry-Esséen bounds and almost sure CLT for the quadratic variation of the sub-fractional Brownian motion

In this paper, we derive explicit bounds for the Kolmogorov distance in the CLT and we prove the almost sure CLT for the quadratic variation of the sub-fractional Brownian motion. We use recent results on the Stein method combined with the Malliavin calculus and an almost sure CLT for multiple integrals.     

Hitting probabilities and the Hausdorff dimension of the inverse images of a class of anisotropic random fields

Let X = {X(t):t ∈ R~N} be an anisotropic random field with values in R~d.Under certain conditions on X,we establish upper and lower bounds on the hitting probabilities of X in terms of respectively Hausdorff measure and Bessel-Riesz capacity.We also obtain the Hausdorff dimension of its inverse image,and the Hausdorff and packing dimensions of its level sets.These results are applicable to non-linear solutions of stochastic heat equations driven by a white in time and spatially homogeneous Gaussian noise and anisotropic Guassian random fields.