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The univariate extreme value theory deals with the convergence in type of powers of elements of sequences of cumulative distribution functions on the real line when the power index gets infinite. In terms of convergence of random variables,…

Probability · Mathematics 2018-10-04 Gane Samb Lo , Modou Ngom , Tchilabola Abozou Kpanzou , Mouminou Diallo

In this paper, we study weak well-posedness of a McKean-Vlasov stochastic differential equations (SDEs) whose drift is density-dependent and whose diffusion is constant. The existence part is due to H\"older stability estimates of the…

Numerical Analysis · Mathematics 2025-11-20 Anh-Dung Le

We show that spline and wavelet series regression estimators for weakly dependent regressors attain the optimal uniform (i.e. sup-norm) convergence rate $(n/\log n)^{-p/(2p+d)}$ of Stone (1982), where $d$ is the number of regressors and $p$…

Statistics Theory · Mathematics 2022-06-06 Xiaohong Chen , Timothy Christensen

The functional linear model extends the notion of linear regression to the case where the response and covariates are iid elements of an infinite dimensional Hilbert space. The unknown to be estimated is a Hilbert-Schmidt operator, whose…

Statistics Theory · Mathematics 2016-12-22 Tung Pham , Victor Panaretos

Here, we study the periodic homogenization problem of nonlinear weakly coupled systems of Hamilton-Jacobi equations in the convex setting. We establish a rate of convergence $O(\sqrt{\varepsilon})$ which is sharp.

Analysis of PDEs · Mathematics 2025-05-20 Hiroyoshi Mitake , Panrui Ni

We consider uniform moment convergence of lag-window spectral density estimates for univariate and multivariate stationary processes. Optimal rates of convergence are obtained under mild and easily verifiable conditions. Our theory…

Methodology · Statistics 2015-05-15 Wei Biao Wu , Paolo Zaffaroni

There exists a wide literature on modelling strongly dependent time series using a longmemory parameter d, including more recent work on semiparametric wavelet estimation. As a generalization of these latter approaches, in this work we…

Statistics Theory · Mathematics 2010-07-28 François Roueff , Rainer Von Sachs

In this contribution we introduce weakly locally stationary time series through the local approximation of the non-stationary covariance structure by a stationary one. This allows us to define autoregression coefficients in a non-stationary…

Statistics Theory · Mathematics 2018-01-16 François Roueff , Andres Sanchez-Perez

The paper studies the rate of convergence of the weak Euler approximation for It\^{o} diffusion and jump processes with H\"{o}lder-continuous generators. It covers a number of stochastic processes including the nondegenerate diffusion…

Probability · Mathematics 2014-01-13 Remigijus Mikulevičius , Changyong Zhang

The extremes of a stationary time series typically occur in clusters. A primary measure for this phenomenon is the extremal index, representing the reciprocal of the expected cluster size. Both a disjoint and a sliding blocks estimator for…

Statistics Theory · Mathematics 2017-07-14 Betina Berghaus , Axel Bücher

We consider a finite element approximation of a general semi-linear stochastic partial differential equation (SPDE) driven by space-time multiplicative and additive noise. We examine the full weak convergence rate of the exponential Euler…

Numerical Analysis · Mathematics 2015-07-28 Antoine Tambue , Jean Medard T. Ngnotchouye

In this paper we analyze the approximation of stable linear time-invariant systems, like the Hilbert transform, by sampling series for bandlimited functions in the Paley-Wiener space $\mathcal{PW}_{\pi}^{1}$. It is known that there exist…

Information Theory · Computer Science 2015-05-13 Holger Boche , Ullrich J. Mönich

We study long time behavior of a discrete time weakly interacting particle system, and the corresponding nonlinear Markov process in $\mathbb{R}^d$, described in terms of a general stochastic evolution equation. In a setting where the state…

Probability · Mathematics 2014-01-16 Amarjit Budhiraja , Abhishek Pal Majumder

We consider estimation of covariance matrices and their inverses (a.k.a. precision matrices) for high-dimensional stationary and locally stationary time series. In the latter case the covariance matrices evolve smoothly in time, thus…

Statistics Theory · Mathematics 2014-01-07 Xiaohui Chen , Mengyu Xu , Wei Biao Wu

For a measure preserving dynamical system $(\mathcal{X},f, \mu)$, we consider the time series of maxima $M_n=\max\{X_1,\ldots,X_n\}$ associated to the process $X_n=\phi(f^{n-1}(x))$ generated by the dynamical system for some observable…

Dynamical Systems · Mathematics 2017-05-25 Mark Holland , Mike Todd

The aim of this paper is to extend the aggregation convergence results given in (Dacunha-Castelle and Fermin 2005, Dacunha-Castelle and Fermin 2008) to doubly stochastic linear and nonlinear processes with weakly dependent innovations.…

Probability · Mathematics 2008-05-15 Lisandro J. Fermin

We are interested in the discretization of stable driven SDEs with additive noise for $\alpha$ $\in$ (1, 2) and Lq -- Lp drift under the Serrin type condition $\alpha$/q + d/p < $\alpha$ -- 1. We show weak existence and uniqueness as well…

Probability · Mathematics 2024-05-15 Mathis Fitoussi , Benjamin Jourdain , Stéphane Menozzi

We study the Lp-integrated risk of some classical estimators of the density, when the observations are drawn from a strictly stationary sequence. The results apply to a large class of sequences, which can be non-mixing in the sense of…

Statistics Theory · Mathematics 2016-05-18 Jérôme Dedecker , Florence Merlevède

The paper studies the rate of convergence of the weak Euler approximation for solutions to possibly completely degenerate SDEs driven by Levy processes, with Hoelder-continuous coefficients. It investigates the dependence of the rate on the…

Probability · Mathematics 2012-05-14 R. Mikulevicius

Predictive equivalence in discrete stochastic processes have been applied with great success to identify randomness and structure in statistical physics and chaotic dynamical systems and to inferring hidden Markov models. We examine the…

Statistical Mechanics · Physics 2021-09-21 Samuel P. Loomis , James P. Crutchfield