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We prove a deviation bound for the maximum of partial sums of functions of $\alpha$-dependent sequences as defined in Dedecker, Gou{\"e}zel and Merlev{\`e}de (2010). As a consequence, we extend the Rosenthal inequality of Rio (2000) for…

Probability · Mathematics 2016-01-22 J Dedecker , Florence Merlevède

We give a Cram\'{e}r moderate deviation expansion for martingales with differences having finite conditional moments of order $2+\rho, \rho \in (0,1],$ and finite one-sided conditional exponential moments. The upper bound of the range of…

Probability · Mathematics 2020-05-11 Xiequan Fan , Ion Grama , Quansheng Liu

We develop a martingale approximation framework yielding quantitative maximal large deviations estimates for invertible dynamical systems. From suitable decay of correlations, we deduce these estimates and, as an application, we obtain…

Dynamical Systems · Mathematics 2026-05-08 José F. Alves , João S. Matias , Ian Melbourne

We study variational regularisation methods for inverse problems with imperfect forward operators whose errors can be modelled by order intervals in a partial order of a Banach lattice. We carry out analysis with respect to existence and…

Numerical Analysis · Mathematics 2020-12-25 Leon Bungert , Martin Burger , Yury Korolev , Carola-Bibiane Schoenlieb

We obtain an uniform tail estimates for natural normed sums of independent random variables (r.v.) with regular varying tails of distributions. We give also many examples on order to show the exactness of offered estimates and discuss some…

Probability · Mathematics 2012-06-22 E. Ostrovsky , L. Sirota

In this paper, we extend the concept of split variational inequality problems from Hilbert spaces to Banach spaces. Then we apply the Fan-KKM theorem to prove the existence of solutions to some split variational inequality problems and some…

Functional Analysis · Mathematics 2015-11-24 Jinlu Li

In this paper non-asymptotic exponential and moment estimates are derived for tail of distribution for discrete time martingale and martingale transform by means of martingale differences in the terms of moments and tails of distributions…

Probability · Mathematics 2012-06-22 E. Ostrovsky , L. Sirota

In this paper we present a tail inequality for the maximum of partial sums of a weakly dependent sequence of random variables that are not necessarily bounded. The class considered includes geometrically and subgeometrically strongly mixing…

Probability · Mathematics 2009-02-04 Florence Merlevède , Magda Peligrad , Emmanuel Rio

We derive various sharp bounds on moments of the distance between two independent random vectors taking values in a Banach space.

Functional Analysis · Mathematics 2019-05-06 Assaf Naor , Krzysztof Oleszkiewicz

(This is the third version of a working paper.) We develop a family of self-normalized concentration inequalities for marginal mean under martingale-difference structure and $\phi/\tilde{\phi}$-mixing conditions, where the latter includes…

Statistics Theory · Mathematics 2025-12-17 Zihao Yuan

The field of algorithmic randomness studies what it means for infinite binary sequences to be random for some given uncertainty model. Classically, martingale-theoretic notions of such randomness involve precise uncertainty models, and it…

Probability · Mathematics 2022-10-10 Floris Persiau , Jasper De Bock , Gert de Cooman

In this paper we derive characterizations of boundedness of the subsequences of partial sums with respect to Vilenkin system on the martingale Hardy spaces when $ 0<p<1 $. Moreover, we find necessary and sufficient conditions for the…

Classical Analysis and ODEs · Mathematics 2018-02-22 G. Tephnadze

We give a proof of the maximal inequalities of Burkholder, Davis and Gundy for real as well as Hilbert-space-valued local martingales using almost only stochastic calculus. Some parts of the exposition, especially in the infinite…

Probability · Mathematics 2013-08-13 Carlo Marinelli , Michael Röckner

While classical concentration inequalities are typically restricted to two special cases -- independence and martingale difference sequences -- we extend concentration inequalities to a much broader class of stochastic processes by relaxing…

Probability · Mathematics 2026-02-25 Changqing Liu

We obtain error rates for large deviations of sums of i.i.d. random variables in, a particular case, of the domain of a non-symmetric infinite mean $\alpha=1$-stable law. The focus of this work is on the method of proof via analytic…

Probability · Mathematics 2025-06-17 Jonny Imbierski , Dalia Terhesiu

We consider the stochastic integrals of multivariate point processes and study their concentration phenomena. In particular, we obtain a Bernstein type of concentration inequality through Dol\'eans-Dade exponential formula and a uniform…

Probability · Mathematics 2017-03-24 Hanchao Wang , Zhengyan Lin , Zhonggen Su

As an alternative to the well-known methods of "chaining" and "bracketing" that have been developed in the study of random fields, a new method, which is based on a stochastic maximal inequality derived by using It\^o's formula and on a new…

Probability · Mathematics 2016-02-12 Yoichi Nishiyama

We obtain some maximal probability and moment inequalities for multidimensionally indexed demimartingales. Although the class of single-indexed demimartingales has been studied extensively, no significant amount of work has been done for…

Probability · Mathematics 2022-10-04 Milto Hadjikyriakou , B. L. S. Prakasa Rao

This paper presents a brief survey of the theory of stochastic integration in Banach spaces. Expositions of the stochastic integrals in martingale type 2 spaces and UMD spaces are presented, as well as some applications of the latter to…

Probability · Mathematics 2014-05-28 Jan van Neerven , Mark Veraar , Lutz Weis

Maximal inequalities refer to bounds on expected values of the supremum of averages of random variables over a collection. They play a crucial role in the study of non-parametric and high-dimensional estimators, and especially in the study…

Probability · Mathematics 2025-04-28 Supratik Basu , Arun K Kuchibhotla
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