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For a class of one-dimensional autoregressive processes $(X_n)$ we consider the tail behaviour of the stopping time $T_0=\min \lbrace n\geq 1: X_n\leq 0 \rbrace$. We discuss existing general analytical approaches to this and related…

Probability · Mathematics 2018-08-01 Günter Hinrichs , Martin Kolb , Vitali Wachtel

We introduce a recursive algorithm of conveniently general form for estimating the coefficient of a moving average model of order one and obtain convergence results for both correct and misspecified MA(1) models. The algorithm encompasses…

Statistics Theory · Mathematics 2007-06-13 James L. Cantor , David F. Findley

We consider a new approach in the definition of two-dimensional heavy-tailed distributions. Namely, we introduce the classes of two-dimensional long-tailed, of twodimensional dominatedly varying and of two-dimensional consistently varying…

Probability · Mathematics 2025-06-25 Dimitrios G. Konstantinides , Charalampos D. Passalidis

We study the continuity properties of trajectories for some random series of functions $\sum a\_kf(\alpha X\_k(\omega))$ where $a\_k$ is a complex sequence, $X\_k$ a sequence of real independent random variables, $f$ is a real valued…

Probability · Mathematics 2016-08-16 Frédéric Paccaut , Dominique Schneider

This paper investigates the stability and convergence properties of asynchronous stochastic approximation (SA) algorithms, with a focus on extensions relevant to average-reward reinforcement learning. We first extend a stability proof…

Machine Learning · Computer Science 2025-12-10 Huizhen Yu , Yi Wan , Richard S. Sutton

Inference over tails is usually performed by fitting an appropriate limiting distribution over observations that exceed a fixed threshold. However, the choice of such threshold is critical and can affect the inferential results. Extreme…

Statistical Finance · Quantitative Finance 2019-02-26 Chiara Lattanzi , Manuele Leonelli

Heavy-tailed fluctuations and power law distributions pervade physics, biology, and the social sciences, with numerous mechanisms proposed for their emergence. Kesten processes, which are multiplicative stochastic recursions with additive…

Chaotic Dynamics · Physics 2026-02-18 Virgile Troude , Didier Sornette

The tail measure of a regularly varying stationary time series has been recently introduced. It is used in this contribution to reconsider certain properties of the tail process and establish new ones. A new formulation of the time change…

Probability · Mathematics 2017-12-01 Hrvoje Planinić , Philippe Soulier

We establish a statistical learning theoretical framework aimed at extrapolation, or out-of-domain generalization, on the unobserved tails of covariates in continuous regression problems. Our strategy involves performing statistical…

Machine Learning · Statistics 2025-09-15 Stephan Clémençon , Nathan Huet , Anne Sabourin

Consider a family of random walks $S_n^{(a)}=X_1^{(a)}+\cdots+X_n^{(a)}$ with negative drift $\mathbf E X_1^{(a)}=-a<0$ and finite variance $\mbox{var}(X_1^{(a)})=\sigma^2<\infty$.Let $M^{(a)}=\max_{n\ge 0} S_n^{(a)}$ be the maximums of the…

Probability · Mathematics 2018-06-29 Denis Denisov , Johannes Kugler

This paper develops and estimates a multivariate affine GARCH(1,1) model with Normal Inverse Gaussian innovations that captures time-varying volatility, heavy tails, and dynamic correlation across asset returns. We generalize the…

Econometrics · Economics 2025-05-20 Ayush Jha , Abootaleb Shirvani , Ali Jaffri , Svetlozar T. Rachev , Frank J. Fabozzi

Cyclic and randomized stepsizes are widely used in the deep learning practice and can often outperform standard stepsize choices such as constant stepsize in SGD. Despite their empirical success, not much is currently known about when and…

Machine Learning · Statistics 2023-08-30 Mert Gürbüzbalaban , Yuanhan Hu , Umut Şimşekli , Lingjiong Zhu

We establish large deviations properties valid for almost every sample path of a class of stationary mixing processes $(X_1,..., X_n,...)$. These properties are inherited from those of $S_n=\sum_{i=1}^nX_i$ and describe how the local…

Probability · Mathematics 2011-12-08 Julien Barral , Patrick Loiseau

In recent years, tensors have been applied to different applications in science and engineering fields. In order to establish theory about tail bounds of the tensors summation behavior, this work extends previous work by considering the…

Probability · Mathematics 2021-10-05 Shih Yu Chang

Several objects in the Extremes literature are special instances of max-stable random sup-measures. This perspective opens connections to the theory of random sets and the theory of risk measures and makes it possible to extend…

Probability · Mathematics 2016-03-18 Ilya Molchanov , Kirstin Strokorb

We consider real-valued random variables R satisfying the distributional equation R \eqdist \sum_{k=1}^{N}T_k R_k + Q, where R_1,R_2,... are iid copies of R and independent of T=(Q, (T_k)_{k \ge 1}). N is the number of nonzero weights T_k…

Probability · Mathematics 2012-06-19 Gerold Alsmeyer , Ewa Damek , Sebastian Mentemeier

Handling multiplicity without losing much power has been a persistent challenge in various fields that often face the necessity of managing numerous statistical tests simultaneously. Recently, $p$-value combination methods based on…

Statistics Theory · Mathematics 2024-02-06 Yeonwoo Rho

The circular and Jacobi ensembles of random matrices have their eigenvalue support on the unit circle of the complex plane and the interval $(0,1)$ of the real line respectively. The averaged value of the modulus of the corresponding…

Mathematical Physics · Physics 2015-06-16 P. J. Forrester , J. P. Keating

Let $(X_t)_{t = 0 }^{\infty}$ be an irreducible reversible discrete time Markov chain on a finite state space $\Omega $. Denote its transition matrix by $P$. To avoid periodicity issues (and thus ensuring convergence to equilibrium) one…

Probability · Mathematics 2018-01-29 Jonathan Hermon , Yuval Peres

Multivariate Analysis (MVA) comprises a family of well-known methods for feature extraction that exploit correlations among input variables of the data representation. One important property that is enjoyed by most such methods is…

Machine Learning · Statistics 2016-09-21 Sergio Muñoz-Romero , Vanessa Gómez-Verdejo , Jerónimo Arenas-García
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