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We provide upper and lower bounds for the mean ${\mathscr M}(H)$ of $\sup_{t\geqslant 0} \{B_H(t) - t\}$, with $B_H(\cdot)$ a zero-mean, variance-normalized version of fractional Brownian motion with Hurst parameter $H\in(0,1)$. We find…

Probability · Mathematics 2023-06-22 Krzysztof Bisewski , Krzysztof Dębicki , Michel Mandjes

The Central Limit Theorem states that, in the limit of a large number of terms, an appropriately scaled sum of independent random variables yields another random variable whose probability distribution tends to a stable distribution. The…

Data Analysis, Statistics and Probability · Physics 2024-04-08 Damián H. Zanette , Inés Samengo

This paper first strictly proved that the growth of the second moment of a large class of Gaussian processes is not greater than power function and the covariance matrix is strictly positive definite. Under these two conditions, the maximum…

Statistics Theory · Mathematics 2022-07-21 Shifei Luo

Here we review and extend central limit theorems for highly chaotic but deterministic semi-dynamical discrete time systems. We then apply these results show how Brownian motion-like results are recovered, and how an Ornstein-Uhlenbeck…

Statistical Mechanics · Physics 2008-04-15 Michael C. Mackey , Marta Tyran-Kaminska

This work focuses on moderate deviations for two-time scale systems with mixed fractional Brownian motion. Our proof uses the weak convergence method which is based on the variational representation formula for mixed fractional Brownian…

Dynamical Systems · Mathematics 2024-03-13 Xiaoyu Yang , Yuzuru Inahama , Yong Xu

We obtain the law of large numbers (LLN) and the central limit theorem (CLT) for weakly dependent non-stationary arrays of random fields with asymptotically unbounded moments. The weak dependence condition for arrays of random fields is…

Statistics Theory · Mathematics 2024-08-15 Yue Pan , Jiazhu Pan

We establish a central limit theorem for partial sums of stationary linear random fields with dependent innovations, and an invariance principle for anisotropic fractional Brownian sheets. Our result is a generalization of the invariance…

Probability · Mathematics 2013-02-14 Yizao Wang

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

Asymptotic expansion is presented for an estimator of the Hurst coefficient of a fractional Brownian motion. For this, a recently developed theory of asymptotic expansion of the distribution of Wiener functionals is applied. The effects of…

Statistics Theory · Mathematics 2022-09-08 Yuliya Mishura , Hayate Yamagishi , Nakahiro Yoshida

Recently, the notion of a quantum acceleration limit has been proposed for any unitary time evolution of quantum systems governed by arbitrary nonstationary Hamiltonians. This limit articulates that the rate of change over time of the…

Quantum Physics · Physics 2026-05-29 Carlo Cafaro , Walid Redjem , Paul M. Alsing , Newshaw Bahreyni , Christian Corda

We study asymptotic error distributions associated with standard approximation scheme for one-dimensional stochastic differential equations driven by fractional Brownian motions. This problem was studied by, for instance, Gradinaru-Nourdin…

Probability · Mathematics 2019-11-27 Shigeki Aida , Nobuaki Naganuma

We investigate the pathwise well-posedness of stochastic evolution equations perturbed by multiplicative Neumann boundary noise, such as fractional Brownian motion for $H\in(1/3,1/2]$. Combining the controlled rough path approach with the…

Probability · Mathematics 2023-10-17 Alexandra Neamtu , Tim Seitz

Let $Z:=\{Z_t,t\geq0\}$ be a stationary Gaussian process. We study two estimators of $\mathbb{E}[Z_0^2]$, namely $\widehat{f}_T(Z):= \frac{1}{T} \int_{0}^{T} Z_{t}^{2}dt$, and $\widetilde{f}_n(Z) :=\frac{1}{n} \sum_{i =1}^{n}…

Statistics Theory · Mathematics 2021-02-10 Soukaina Douissi , Khalifa Es-Sebaiy , George Kerchev , Ivan Nourdin

The purpose of this paper is twofold. In one direction, we extend the spectral method for random piecewise expanding and hyperbolic dynamics developed by the first author \textit{et al}. to establish quenched versions of the large deviation…

Dynamical Systems · Mathematics 2020-12-02 Davor Dragičević , Yeor Hafouta

In this article, we present the least squares estimator for the drift parameter in a linear regression model driven by the increment of a fractional Brownian motion sampled at random times. For two different random times, Jittered and…

Statistics Theory · Mathematics 2019-02-25 Héctor Araya , Natalia Bahamonde , Lisandro Fermín , Tania Roa , Soledad Torres

The central limit theorem of martingales is the fundamental tool for studying the convergence of stochastic processes, especially stochastic integrals and differential equations. In this paper, general central limit theorems and functional…

Probability · Mathematics 2020-05-08 Li-Xin Zhang

We study the many body quantum evolution of bosonic systems in the mean field limit. The dynamics is known to be well approximated by the Hartree equation. So far, the available results have the form of a law of large numbers. In this paper…

Mathematical Physics · Physics 2012-03-27 Gerard Ben Arous , Kay Kirkpatrick , Benjamin Schlein

We investigate the problem of the rate of convergence to equilibrium for ergodic stochastic differential equations driven by fractional Brownian motion with Hurst parameter $H\in (1/3,1)$ and multiplicative noise component $\sigma$. When…

Probability · Mathematics 2016-10-05 Aurélien Deya , Fabien Panloup , Samy Tindel

Sensitivity analysis w.r.t. the long-range/memory noise parameter for probability distributions of functionals of solutions to stochastic differential equations is an important stochastic modeling issue in many applications. In this paper…

Probability · Mathematics 2024-08-30 Alexandre Richard , Denis Talay

For a L\'evy basis $L$ on $\mathbb{R}^d$ and a suitable kernel function $f:\mathbb{R}^d \to \mathbb{R}$, consider the continuous spatial moving average field $X=(X_t)_{t\in \mathbb{R}^d}$ defined by $X_t = \int_{\mathbb{R}^d} f(t-s) \,…

Probability · Mathematics 2021-08-02 David Berger
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