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In this paper, we will first give the numerical simulation of the sub-fractional Brownian motion through the relation of fractional Brownian motion instead of its representation of random walk. In order to verify the rationality of this…

Probability · Mathematics 2021-01-11 Chunhao Cai , Qinghua Wang , Weilin Xiao

We revise the Levy's construction of Brownian motion as a simple though still rigorous approach to operate with various Gaussian processes. A Brownian path is explicitly constructed as a linear combination of wavelet-based "geometrical…

Statistical Mechanics · Physics 2020-01-03 Denis S. Grebenkov , Dmitry Beliaev , Peter W. Jones

Let R be a symmetric a-stable Riemann-Liouville process with Hurst parameter H > 0. Consider ||.|| a translation invariant, b-self-similar, and p-pseudo-additive functional semi-norm. We show that if H > (b + 1/p) and c = (H - b - 1/p),…

Probability · Mathematics 2015-06-26 Mikhail. A. Lifshits , Thomas Simon

Exact and asymptotic formulas relating to dynamical correlations for overdamped Brownian motion are obtained. These formulas include a generalization of the $f$-sum rule from the theory of quantum fluids, a formula relating the static…

Statistical Mechanics · Physics 2015-06-25 P. J. Forrester , B. Jancovici

The present article is devoted to a fine study of the convergence of renormalized weighted quadratic and cubic variations of a fractional Brownian motion $B$ with Hurst index $H$. In the quadratic (resp. cubic) case, when $H<1/4$ (resp.…

Probability · Mathematics 2009-01-19 Ivan Nourdin

In this work we study two Riemannian distances between infinite-dimensional positive definite Hilbert-Schmidt operators, namely affine-invariant Riemannian and Log-Hilbert-Schmidt distances, in the context of covariance operators associated…

Machine Learning · Statistics 2021-08-27 Ha Quang Minh

The strong $L^2$-approximation of occupation time functionals is studied with respect to discrete observations of a $d$-dimensional c\`adl\`ag process. Upper bounds on the error are obtained under weak assumptions, generalizing previous…

Probability · Mathematics 2021-02-02 Randolf Altmeyer

Let $B^{a,b}:=\{B_t^{a,b},t\geq0\}$ be a weighted fractional Brownian motion of parameters $a>-1$, $|b|<1$, $|b|<a+1$. We consider a least square-type method to estimate the drift parameter $\theta>0$ of the weighted fractional…

Probability · Mathematics 2020-11-02 Abdulaziz Alsenafi , Mishari Al-Foraih , Khalifa Es-Sebaiy

This article provides an overview of recent work on descriptions and properties of the convex minorant of random walks and L\'evy processes which summarize and extend the literature on these subjects. The results surveyed include point…

Probability · Mathematics 2012-11-16 Josh Abramson , Jim Pitman , Nathan Ross , Gerónimo Uribe Bravo

We study boundary non-crossing probabilities $$ P_{f,u} := \mathrm P\big(\forall t\in \mathbb T\ X_t + f(t)\le u(t)\big) $$ for continuous centered Gaussian process $X$ indexed by some arbitrary compact separable metric space $\mathbb T$.…

Probability · Mathematics 2020-03-16 Enkelejd Hashorva , Yuliya Mishura , Georgiy Shevchenko

In this note, we study the asymptotical frontier behavior of a branching reflected Brownian motion. There is essentially no difference in maximal displacement between a branching Brownian motion and its reflected counterpart. We provide two…

Probability · Mathematics 2014-04-07 Wenpin Tang

We survey existing results concerning the study in small times of the density of the solution of a rough differential equation driven by fractional Brownian motions. We also slightly improve existing results and discuss some possible…

Probability · Mathematics 2014-03-05 Fabrice Baudoin , Cheng Ouyang

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

This contribution establishes exact tail asymptotics of $\sup_{(s,t)\in\mathbf{E}}$ $X(s,t)$ for a large class of nonhomogeneous Gaussian random fields $X$ on a bounded convex set $\mathbf{E}\subset\mathbb{R}^2$, with variance function that…

Probability · Mathematics 2016-03-16 Krzysztof Dȩbicki , Enkelejd Hashorva , Lanpeng Ji

We obtain exact asymptotic results for the disorder averaged persistence of a Brownian particle moving in a biased Sinai landscape. We employ a new method that maps the problem of computing the persistence to the problem of finding the…

Statistical Mechanics · Physics 2009-11-07 Satya N. Majumdar , Alain Comtet

We consider the problem of estimating a smooth functional of an unknown signal with discontinuity from Gaussian observations. The signal is a known function that depends on an unknown parameter. This problem is closely related to the famous…

Statistics Theory · Mathematics 2011-12-19 Farida Enikeeva

Linear thresholding models postulate that the conditional distribution of a response variable in terms of covariates differs on the two sides of a (typically unknown) hyperplane in the covariate space. A key goal in such models is to learn…

Statistics Theory · Mathematics 2021-10-01 Debarghya Mukherjee , Moulinath Banerjee , Debasri Mukherjee , Ya'acov Ritov

A parameter estimation problem is considered, in which dispersed sensors transmit to the statistician partial information regarding their observations. The sensors observe the paths of continuous semimartingales, whose drifts are linear…

Methodology · Statistics 2013-02-01 Georgios Fellouris

Let $B=\{(B_{t}^{1},..., B_{t}^{d}), t\geq 0\}$ be a $d$-dimensional fractional Brownian motion with Hurst parameter $H$ and let $R_{t}=% \sqrt{(B_{t}^{1})^{2}+... +(B_{t}^{d})^{2}}$ be the fractional Bessel process. It\^{o}'s formula for…

Probability · Mathematics 2007-05-23 Yaozhong Hu , David Nualart

This paper proposes a new formulation of functional Gaussian Process regression in manifolds, based on an Empirical Bayes approach, in the spatiotemporal random field context. We apply the machinery of tight Gaussian measures in separable…

Machine Learning · Statistics 2026-03-24 MD Ruiz-Medina , AE Madrid , A Torres-Signes , JM Angulo