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We propose a general framework for regularization in M-estimation problems under time dependent (absolutely regular-mixing) data which encompasses many of the existing estimators. We derive non-asymptotic concentration bounds for the…

Statistics Theory · Mathematics 2018-01-04 Demian Pouzo

General Central limit theorem deals with weak limits (in type) of sums of row-elements of array random variables. In some situations as in the invariance principle problem, the sums may include only parts of the row-elements. For strictly…

We establish asymptotic normality of weighted sums of periodograms of a stationary linear process where weights depend on the sample size. Such sums appear in numerous statistical applications and can be regarded as a discretized versions…

Statistics Theory · Mathematics 2013-12-18 Liudas Giraitis , Hira L. Koul

Max-stable random fields are very appropriate for the statistical modelling of spatial extremes. Hence, integrals of functions of max-stable random fields over a given region can play a key role in the assessment of the risk of natural…

Probability · Mathematics 2018-07-25 Erwan Koch , Clément Dombry , Christian Y. Robert

The paper considers the properties of pseudo stationarity in a broad sense and pseudo strong mixing for sequences of random variables corresponding to arithmetic functions. Assertions on this topic have been proven. The implementation of…

Number Theory · Mathematics 2019-06-19 Victor Volfson

We study the asymptotic joint distribution of sample space--time covariance estimators of strictly stationary random fields. We do this without any marginal or joint distributional assumptions other than mild moment and mixing conditions.…

Statistics Theory · Mathematics 2008-12-18 Bo Li , Marc G. Genton , Michael Sherman

We investigate asymptotic behaviour of probabilities of large deviations for normalized combinatorial sums. We find a zone in which these probabilities are equivalent to the tail of the standard normal law. Our conditions are similar to the…

Probability · Mathematics 2019-01-15 Andrei N. Frolov

Stochastic gradient algorithms are more and more studied since they can deal efficiently and online with large samples in high dimensional spaces. In this paper, we first establish a Central Limit Theorem for these estimates as well as for…

Statistics Theory · Mathematics 2017-10-17 Antoine Godichon-Baggioni

In this paper we show a central limit theorem for Lebesgue integrals of stationary $BL(\theta)$-dependent random fields as the integration domain grows in Van Hove-sense. Our method is to use the (known) analogue result for discrete sums.…

Probability · Mathematics 2016-01-05 Jürgen Kampf

We study conditions under which treatment effect estimators constructed under the no-interference assumption in randomized experiments are asymptotically normal in the presence of interference. We prove that the standard Horvitz-Thompson…

Statistics Theory · Mathematics 2019-03-08 Alex Chin

We analyze the asymptotic fluctuations of linear eigenvalue statistics of random centrosymmetric matrices with i.i.d. entries. We prove that for a complex analytic test function, the centered and normalized linear eigenvalue statistics of…

Probability · Mathematics 2025-10-20 Indrajit Jana , Sunita Rani

For nonstationary, strongly mixing sequences of random variables taking their values in a finite-dimensional Euclidean space, with the partial sums being normalized via matrix multiplication, with certain standard conditions being met, the…

Probability · Mathematics 2021-09-07 Richard C. Bradley , Zbigniew J. Jurek

We obtain an almost sure limit theorem for the maximum of nonstationary random fields under some dependence conditions.

Probability · Mathematics 2016-01-07 Luísa Pereira , Zhongquan Tan

Central limit theorems for the log-volume of a class of random convex bodies in $\mathbb{R}^n$ are obtained in the high-dimensional regime, that is, as $n\to\infty$. In particular, the case of random simplices pinned at the origin and…

In this paper, we study the asymptotic behavior of a semi-linear slow-fast stochastic partial differential equation with singular coefficients. Using the Poisson equation in Hilbert space, we first establish the strong convergence in the…

Probability · Mathematics 2021-06-09 Michael Röckner , Longjie Xie , Li Yang

This paper deals with the spatial and temporal regularity of the unique Hilbert space valued mild solution to a semilinear stochastic partial differential equation with nonlinear terms that satisfy global Lipschitz conditions. It is shown…

Analysis of PDEs · Mathematics 2012-08-21 Raphael Kruse , Stig Larsson

We consider perturbed nonlinear ill-posed equations in Hilbert spaces, with operators that are monotone on a given closed convex subset. A simple stable approach is Lavrentiev regularization, but existence of solutions of the regularized…

Numerical Analysis · Mathematics 2018-06-05 Robert Plato , Bernd Hofmann

We study infinite systems of mean field weakly coupled intermittent maps in the Pomeau-Manneville scenario. We prove that the coupled system admits a unique ``physical'' stationary state, to which all absolutely continuous states converge.…

Dynamical Systems · Mathematics 2023-07-18 Wael Bahsoun , Alexey Korepanov

Regularity estimates for an integral operator with a symmetric continuous kernel on a convex bounded domain are derived. The covariance of a mean-square continuous random field on the domain is an example of such an operator. The estimates…

Probability · Mathematics 2022-04-25 Mihály Kovács , Annika Lang , Andreas Petersson

We present a Hilbert space perspective to homogenization of standard linear evolutionary boundary value problems in mathematical physics and provide a unified treatment for (non-)periodic homogenization problems in thermodynamics,…

Analysis of PDEs · Mathematics 2016-03-08 Marcus Waurick