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Bayesian nonparametric regression under a rescaled Gaussian process prior offers smoothness-adaptive function estimation with near minimax-optimal error rates. Hierarchical extensions of this approach, equipped with stochastic variable…

Statistics Theory · Mathematics 2020-12-15 Sheng Jiang , Surya T. Tokdar

We describe an elementary method to get non-asymptotic estimates for the moments of Hermitian random matrices whose elements are Gaussian independent random variables. As the basic example, we consider the GUE matrices. Immediate…

Mathematical Physics · Physics 2007-05-23 O. Khorunzhiy

Concentration inequalities quantify the deviation of a random variable from a fixed value. In spite of numerous applications, such as opinion surveys or ecological counting procedures, few concentration results are known for the setting of…

Statistics Theory · Mathematics 2015-07-28 Rémi Bardenet , Odalric-Ambrym Maillard

We present some extensions of Bernstein's concentration inequality for random matrices. This inequality has become a useful and powerful tool for many problems in statistics, signal processing and theoretical computer science. The main…

Probability · Mathematics 2017-04-18 Stanislav Minsker

In this paper, we study the asymptotic distribution of the maxima of suprema of dependent Gaussian processes with trend. For different scales of the time horizon we obtain different normalizing functions for the convergence of the maxima.…

Probability · Mathematics 2022-11-09 Lanpeng Ji , Xiaofan Peng

We investigate the sub-Gaussian property for almost surely bounded random variables. If sub-Gaussianity per se is de facto ensured by the bounded support of said random variables, then exciting research avenues remain open. Among these…

Probability · Mathematics 2019-07-16 Julyan Arbel , Olivier Marchal , Hien D. Nguyen

We obtain almost sure limit theorems for partial maxima of norms of a sequence of Banach-valued Gaussian random variables.

Probability · Mathematics 2018-02-22 James Kuelbs , Joel Zinn

This paper studies large sample properties of a Bayesian approach to inference about slope parameters $\gamma$ in linear regression models with a structural break. In contrast to the conventional approach to inference about $\gamma$ that…

Econometrics · Economics 2023-08-15 Kenichi Shimizu

We consider the semi-parametric estimation of a scale parameter of a one-dimensional Gaussian process with known smoothness. We suggest an estimator based on quadratic variations and on the moment method. We provide asymptotic…

Statistics Theory · Mathematics 2020-01-22 Jean-Marc Azaïs , François Bachoc , Agnès Lagnoux , Thi Mong Ngoc Nguyen

This paper develops a new direct approach to approximating suprema of general empirical processes by a sequence of suprema of Gaussian processes, without taking the route of approximating whole empirical processes in the sup-norm. We prove…

Probability · Mathematics 2014-08-19 Victor Chernozhukov , Denis Chetverikov , Kengo Kato

We obtain a Bernstein-type inequality for sums of Banach-valued random variables satisfying a weak dependence assumption of general type and under certain smoothness assumptions of the underlying Banach norm. We use this inequality in order…

Machine Learning · Statistics 2018-12-11 Gilles Blanchard , Oleksandr Zadorozhnyi

Seemingly unrelated linear regression models are introduced in which the distribution of the errors is a finite mixture of Gaussian components. Identifiability conditions are provided. The score vector and the Hessian matrix are derived.…

Methodology · Statistics 2014-03-18 Giuliano Galimberti , Elena Scardovi , Gabriele Soffritti

Spectral properties of Gram matrices are central to high dimensional asymptotic analyses of statistical estimators in regression and covariance estimation. These properties, in turn, depend critically on the extreme singular values and…

Statistics Theory · Mathematics 2026-03-03 Partha Sarkar , Kshitij Khare , Sanvesh Srivastava

We present a generalization of the maximal inequalities that upper bound the expectation of the maximum of $n$ jointly distributed random variables. We control the expectation of a randomly selected random variable from $n$ jointly…

Probability · Mathematics 2017-08-31 Jiantao Jiao , Yanjun Han , Tsachy Weissman

In this paper we prove exponential inequalities (also called Bernstein's inequality) for fractional martingales. As an immediate corollary, we will discuss weak law of large numbers for fractional martingales under divergence assumption on…

Probability · Mathematics 2012-04-20 Bruno Saussereau

The seminal papers of Pickands [1,2] paved the way for a systematic study of high exceedance probabilities of both stationary and non-stationary Gaussian processes. Yet, in the vector-valued setting, due to the lack of key tools including…

Probability · Mathematics 2019-11-18 Krzysztof Dȩbicki , Enkelejd Hashorva , Longmin Wang

We consider the problem of detecting an elevated mean on an interval with unknown location and length in the univariate Gaussian sequence model. Recent results have shown that using scale-dependent critical values for the scan statistic…

Statistics Theory · Mathematics 2021-07-20 Guenther Walther , Andrew Perry

An isoperimetric inequality on the Hamming cube for exponents $\beta\ge 0.50057$ is proved, achieving equality on any subcube. This was previously known for $\beta\ge \log_2(3/2)\approx 0.585$. Improved bounds are also obtained at the…

Classical Analysis and ODEs · Mathematics 2024-07-18 Polona Durcik , Paata Ivanisvili , Joris Roos

Gaussian random fields on Euclidean spaces whose variances reach their maximum values at unique points are considered. Exact asymptotic behaviors of probabilities of large absolute maximum of theirs trajectories have been evaluated using…

Probability · Mathematics 2019-04-12 Sergey G. Kobelkov , Vladimir I. Piterbarg

We investigate a classical statistical model and show that Mermin's version of a Bell inequality is violated. We get this violation, if the measurement modifies the ensemble, a feature, which is also characteristic for measurement processes…

Quantum Physics · Physics 2019-07-02 Manfried Faber