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Recently, various models have been developed, including the fractional Brownian motion (fBm), to analyse the stochastic properties of geodetic time series, together with the extraction of geophysical signals. The noise spectrum of these…

Methodology · Statistics 2021-02-18 J. P. Montillet , X. He , K. Yu

In certain applications, for instance biomechanics, turbulence, finance, or Internet traffic, it seems suitable to model the data by a generalization of a fractional Brownian motion for which the Hurst parameter $H$ is depending on the…

Statistics Theory · Mathematics 2007-06-13 Jean-Marc Bardet , Pierre Bertrand

In this paper we are interested in multifractional stable processes where the self-similarity index $H$ is a function of time, in other words $H$ becomes time changing, and the stability index $\alpha$ is a constant. Using $\beta$- negative…

Statistics Theory · Mathematics 2017-11-23 Thi To Nhu Dang

Starting from the notion of multivariate fractional Brownian Motion introduced in [F. Lavancier, A. Philippe, and D. Surgailis. Covariance function of vector self-similar processes. Statistics & Probability Letters, 2009] we define a…

Probability · Mathematics 2025-09-16 Ranieri Dugo , Giacomo Giorgio , Paolo Pigato

This article studies typical dynamics and fluctuations for a slow-fast dynamical system perturbed by a small fractional Brownian noise. Based on an ergodic theorem with explicit rates of convergence, which may be of independent interest, we…

Probability · Mathematics 2020-08-20 Solesne Bourguin , Siragan Gailus , Konstantinos Spiliopoulos

In this paper, we consider the problem of estimating the lead-lag parameter between two stochastic processes driven by fractional Brownian motions (fBMs) of the Hurst parameter greater than 1/2. First we propose a lead-lag model between two…

Statistics Theory · Mathematics 2018-03-13 Kohei Chiba

We consider the sum of two self-similar centred Gaussian processes with different self-similarity indices. Under non-negativity assumptions of covariance functions and some further minor conditions, we show that the asymptotic behaviour of…

Probability · Mathematics 2022-06-27 Frank Aurzada , Martin Kilian , Ercan Sönmez

Scaling properties of time series are usually studied in terms of the scaling laws of empirical moments, which are the time average estimates of moments of the dynamic variable. Nonlinearities in the scaling function of empirical moments…

Probability · Mathematics 2023-04-24 Marco Zamparo

We introduce a class of Gaussian processes with stationary increments which exhibit long-range dependence. The class includes fractional Brownian motion with Hurst parameter H>1/2 as a typical example. We establish infinite and finite past…

Probability · Mathematics 2011-11-10 Akihiko Inoue , Vo Van Anh

We consider a problem of statistical estimation of an unknown drift parameter for a stochastic differential equation driven by fractional Brownian motion. Two estimators based on discrete observations of solution to the stochastic…

Probability · Mathematics 2013-09-26 Yuliya Mishura , Kostiantyn Ral'chenko , Oleg Seleznev , Georgiy Shevchenko

Fractional Brownian motion (fBm) is a canonical model for long-memory phenomena. In the presence of large amounts of potentially memory-bearing data, the data are often averaged, which can change the structure of the underlying…

We provide asymptotic results and develop high frequency statistical procedures for time-changed L\'evy processes sampled at random instants. The sampling times are given by first hitting times of symmetric barriers whose distance with…

Probability · Mathematics 2010-07-20 Mathieu Rosenbaum , Peter Tankov

We consider Langevin equation involving fractional Brownian motion with Hurst index $H\in(0,\frac12)$. Its solution is the fractional Ornstein-Uhlenbeck process and with unknown drift parameter $\theta$. We construct the estimator that is…

Probability · Mathematics 2015-01-20 Kestutis Kubilius , Yuliya Mishura , Kostiantyn Ralchenko , Oleg Seleznjev

This paper addresses the problem of estimating the Hurst exponent of the fractional Brownian motion from continuous time noisy sample. Consistent estimation in the setup under consideration is possible only if either the length of the…

Statistics Theory · Mathematics 2023-10-09 P. Chigansky , M. Kleptsyna

This paper addresses the problem of estimating drift parameter of the Ornstein - Uhlenbeck type process, driven by the sum of independent standard and fractional Brownian motions. The maximum likelihood estimator is shown to be consistent…

Probability · Mathematics 2018-08-03 Pavel Chigansky , Marina Kleptsyna

The fractional stable motion is a prototypical stochastic process exhibiting both heavy tails and long-range dependence, parameterized via a stability index $\alpha$ and a Hurst exponent $H$. We consider a nonstationary extension where the…

Probability · Mathematics 2026-05-01 Fabian Mies , Duuk Sikkens

Properties of mixed fractional Brownian motion has been discussed by Cheridito (2001) and Zili (2006). We have proposed an estimator of volatility parameter for a model driven by MFBM. In our article we have shown that the estimator has…

Statistics Theory · Mathematics 2017-06-29 Ananya Lahiri

Consider an estimation of the Hurst parameter $H\in(0,1)$ and the volatility parameter $\sigma>0$ for a fractional Brownian motion with a drift term under high-frequency observations with a finite time interval. In the present paper, we…

Statistics Theory · Mathematics 2022-06-13 Tetsuya Takabatake

The fractional Brownian motion can be considered as a Gaussian field indexed by $(t,H)\in {\mathbb{R}_{+}\times (0,1)}$, where $H$ is the Hurst parameter. On compact time intervals, it is known to be almost surely jointly H\"older…

Probability · Mathematics 2025-02-06 El Mehdi Haress , Alexandre Richard

Strongly consistent and asymptotically normal estimators of the Hurst index and volatility parameters of solutions of stochastic differential equations with polynomial drift are proposed. The estimators are based on discrete observations of…

Probability · Mathematics 2015-05-19 Kestutis Kubilius , Viktor Skorniakov , Dmitrij Melichov