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The extreme value dependence of regularly varying stationary time series can be described by the spectral tail process. Drees, Segers and Warchol [Extremes 18(3): 369--402, 2015] proposed estimators of the marginal distributions of this…

Statistics Theory · Mathematics 2019-07-23 Holger Drees , Miran Knezevic

We study the Central Limit Theorem (CLT) in the so-called mixed (anisotropic) Lebesgue-Riesz spaces and tail behavior of normed sums of centered random independent variables (vectors) with values in these spaces.

Probability · Mathematics 2013-08-27 E. Ostrovsky , L. Sirota

We obtain asymptotic approximations for the probability density function of the product of two correlated normal random variables with non-zero means and arbitrary variances. As a consequence, we deduce asymptotic approximations for the…

Probability · Mathematics 2024-10-22 Robert E. Gaunt , Zixin Ye

We prove Fuk-Nagaev and Rosenthal-type inequalities for sums of independent random matrices, focusing on the situation when the norms of the matrices possess finite moments of only low orders. Our bounds depend on the ``intrinsic''…

Probability · Mathematics 2025-11-20 Moritz Jirak , Stanislav Minsker , Yiqiu Shen , Martin Wahl

Sums of independent, bounded random variables concentrate around their expectation approximately as well a Gaussian of the same variance. Well known results of this form include the Bernstein, Hoeffding, and Chernoff inequalities and many…

Discrete Mathematics · Computer Science 2017-04-25 Thomas Steinke , Jonathan Ullman

In some fields of applications of stable distributions, especially in economics, it appears, that data have distributions similar to stable in a large region, but do not have such heavy tails. Our aim in this note is to propose several…

Probability · Mathematics 2014-03-17 Lenka Slámová , Lev B. Klebanov

We study p-adic counterparts of stable distributions, that is limit distributions for sequences of normalized sums of independent identically distributed p-adic-valued random variables. In contrast to the classical case, non-degenerate…

Probability · Mathematics 2007-05-23 Anatoly N. Kochubei

We study the joint laws of a continuous, uniformly integrable martingale, its maximum, and its minimum. In particular, we give explicit martingale inequalities which provide upper and lower bounds on the joint exit probabilities of a…

Probability · Mathematics 2015-03-31 Alexander M. G. Cox , Jan Obłój

This paper is concerned with the limiting spectral behaviors of large dimensional Kendall's rank correlation matrices generated by samples with independent and continuous components. We do not require the components to be identically…

Statistics Theory · Mathematics 2019-12-16 Zeng Li , Qinwen Wang , Runze Li

We investigate a class of stochastic fragmentation processes involving stable and unstable fragments. We solve analytically for the fragment length density and find that a generic algebraic divergence characterizes its small-size tail.…

Statistical Mechanics · Physics 2007-05-23 P. L. Krapivsky , E. Ben-Naim , I. Grosse

Ratios of quadratic forms in correlated normal variables which introduce noncentrality into the quadratic forms are considered. The denominator is assumed to be positive (with probability 1). Various serial correlation estimates such as…

Statistics Theory · Mathematics 2008-12-18 Ronald W. Butler , Marc S. Paolella

We prove uniform convergence results for the integrated periodogram of a weakly dependent time series, namely a law of large numbers and a central limit theorem. These results are applied to Whittle's parametric estimation. Under general…

Statistics Theory · Mathematics 2008-04-15 Jean-Marc Bardet , Paul Doukhan , José Rafael León

In this paper, we study a method to sample from a target distribution $\pi$ over $\mathbb{R}^d$ having a positive density with respect to the Lebesgue measure, known up to a normalisation factor. This method is based on the Euler…

Statistics Theory · Mathematics 2016-12-20 Alain Durmus , Eric Moulines

We present novel martingale concentration inequalities for martingale differences with finite Orlicz-$\psi_\alpha$ norms. Such martingale differences with weak exponential-type tails scatters in many statistical applications and can be…

Probability · Mathematics 2020-03-19 Chris Junchi Li

In this paper, we develop the lower and upper bounds of worst-case distortion riskmetrics and weighted entropy for unimodal, and symmetric unimodal distributions when mean and variance information are available. We also consider the sharp…

Risk Management · Quantitative Finance 2025-11-24 Baishuai Zuo , Chuancun Yin

Numerous robust estimators exist as alternatives to the maximum likelihood estimator (MLE) when a completely observed ground-up loss severity sample dataset is available. However, the options for robust alternatives to MLE become…

Methodology · Statistics 2024-02-22 Chudamani Poudyal

We introduce the \textsc{Tailed-Uniform} proposal distribution for generating training simulations in simulation-based inference. Instead of sampling parameters uniformly within bounded regions, we extend the distribution beyond prior…

Instrumentation and Methods for Astrophysics · Physics 2026-01-27 Chaipat Tirapongprasert , Matthew Ho

An explicit upper bound on the tail probabilities for the normalized Rademacher sums is given. This bound, which is best possible in a certain sense, is asymptotically equivalent to the corresponding tail probability of the standard normal…

Probability · Mathematics 2017-01-17 Iosif Pinelis

We provide a systematic approach for deducing statistical limit laws via martingale-coboundary decomposition, for nonuniformly hyperbolic systems with slowly contracting and expanding directions. In particular, if the associated return time…

Dynamical Systems · Mathematics 2016-03-11 Ian Melbourne , Paulo Varandas

Different questions related with analysis of extreme values and outliers arise frequently in practice. To exclude extremal observations and outliers is not a good decision because they contain important information about the observed…

Methodology · Statistics 2018-01-17 Pavlina K. Jordanova , Monika P. Petkova