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In this work, we study the class of stochastic process that generalizes the Ornstein-Uhlenbeck processes, hereafter called by \emph{Generalized Ornstein-Uhlenbeck Type Process} and denoted by GOU type process. We consider them driven by the…

Statistics Theory · Mathematics 2021-08-17 J. Stein , S. R. C. Lopes , A. V. Medino

It is considered Ornstein-Uhlenbeck process $ x_t = x_0 e^{-\theta t} + \mu (1-e^{-\theta t}) + \sigma \int_0^t e^{-\theta (t-s)} dW_s$, where $x_0 \in R$, $\theta>0$, $ \mu \in R$ and $\sigma > 0$ are parameters. By use values $(z_k)_{k…

Statistics Theory · Mathematics 2016-08-30 Levan Labadze , Gogi Pantsulaia

Under certain mild conditions, some limit theorems for functionals of two independent Gaussian processes are obtained. The results apply to general Gaussian processes including fractional Brownian motion, sub-fractional Brownian motion and…

Probability · Mathematics 2018-01-30 Jian Song , Fangjun Xu , Qian Yu

The characteristic feature of semi-selfsimilar process is the invariance of its finite dimensional distributions by certain dilation for specific scaling factor. Estimating the scale parameter $\lambda$ and the Hurst index of such processes…

Statistics Theory · Mathematics 2012-07-11 Saeid Rezakhah , Anne Philippe , Navideh Modarresi

In this paper we will consider the LAN property for both the Hurst parameter $H>3/4$ and the variance of the fractional Brownian motion plus an independent standard Brownian motion (called mixed fractional Brownian motion) with…

Probability · Mathematics 2026-01-21 Chunhao Cai , Yiwu Shang

This paper consider the LAN property for the mixed O-U process under high-frequency observation when H>3/4. As considered in mixed fractional Brownian motion, we will also use the projection step to get the non-diagonal rate matrix.

Statistics Theory · Mathematics 2026-03-18 Chunhao Cai , Yiwu Shang , Cong Zhang

We are interested in the law of the first passage time of an Ornstein-Uhlenbeck process to time-varying thresholds. We show that this problem is connected to the laws of the first passage time of the process to members of a two-parameter…

Probability · Mathematics 2024-03-26 Aria Ahari , Larbi Alili , Massimiliano Tamborrino

We characterise the nonequilibrium stationary state of a generic multivariate Ornstein-Uhlenbeck process involving $N$ degrees of freedom. The irreversibility of the process is encoded in the antisymmetric part of the Onsager matrix. The…

Statistical Mechanics · Physics 2018-12-19 Claude Godrèche , Jean-Marc Luck

Using structures of Abstract Wiener Spaces, we define a fractional Brownian field indexed by a product space $(0,1/2] \times L^2(T,m)$, $(T,m)$ a separable measure space, where the first coordinate corresponds to the Hurst parameter of…

Probability · Mathematics 2014-04-24 Alexandre Richard

We study the two-dimensional fractional Brownian motion with Hurst parameter $H>{1/2}$. In particular, we show, using stochastic calculus, that this process admits a skew-product decomposition and deduce from this representation some…

Probability · Mathematics 2007-05-23 Fabrice Baudoin , David Nualart

Moving average processes driven by exponential-tailed L\'evy noise are important extensions of their Gaussian counterparts in order to capture deviations from Gaussianity, more flexible dependence structures, and sample paths with jumps.…

Statistics Theory · Mathematics 2023-08-01 Zhongwei Zhang , David Bolin , Sebastian Engelke , Raphaël Huser

In this contribution, we extend the methodology proposed in Abry and Didier (2017) to obtain the first joint estimator of the real parts of the Hurst eigenvalues of $n$-variate OFBM. The procedure consists of a wavelet regression on the…

Statistics Theory · Mathematics 2017-08-14 Patrice Abry , Gustavo Didier

The diversity of diffusive systems exhibiting long-range correlations characterized by a stochastically varying Hurst exponent calls for a generic multifractional model. We present a simple, analytically tractable model which fills the gap…

We study the stationary fluctuations of independent run-and-tumble particles. We prove that the joint densities of particles with given internal state converges to an infinite dimensional Ornstein-Uhlenbeck process. We also consider an…

Probability · Mathematics 2024-03-13 Frank Redig , Hidde van Wiechen

We investigate the stochastic processes obtained as the fractional Riemann-Liouville integral of order $\alpha \in (0,1)$ of Gauss-Markov processes. The general expressions of the mean, variance and covariance functions are given. Due to…

Probability · Mathematics 2019-05-21 Mario Abundo , Enrica Pirozzi

Let the Ornstein-Uhlenbeck process $\{X_t,\,t\geq 0\}$ driven by a fractional Brownian motion $B^H$ described by $d X_t=-\theta X_t dt+ d B_t^H,\, X_0=0$ with known parameter $H\in (0,\frac34)$ be observed at discrete time instants $t_k=kh,…

Probability · Mathematics 2025-10-21 Zheng Tang , Ying Li , Haili Yang , Hua Yi , Yong Chen

Many physical and biological systems rely on the progression of material through multiple independent stages. In viral replication, for example, virions enter a cell to undergo a complex process comprising several disparate stages before…

Molecular Networks · Quantitative Biology 2024-04-03 Alexander P Browning , Adrianne L Jenner , Ruth E Baker , Philip K Maini

An $N$-particle system with stochastic interactions is considered. Interactions are driven by a Brownian noise term and total energy conservation is imposed. The evolution of the system, in velocity space, is a diffusion on a…

Mathematical Physics · Physics 2013-08-16 Bruno Vieira Ribeiro , Yves Elskens

Multifractional Brownian motion is an extension of the well-known fractional Brownian motion where the Holder regularity is allowed to vary along the paths. In this paper, two kind of multi-parameter extensions of mBm are studied: one is…

Probability · Mathematics 2007-05-23 E. Herbin

Strongly consistent and asymptotic normal estimators of the Hurst index of a stochastic differential equation driven by a fractional Brownian motion are proposed. The estimators are based on discrete observations of the underlying process.

Probability · Mathematics 2014-02-18 K. Kubilius , V. Skorniakov , D. Melichov