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Related papers: Probabilities for asymmetric p-outside values

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The issue of combining individual $p$-values to aggregate multiple small effects is prevalent in many scientific investigations and is a long-standing statistical topic. Many classical methods are designed for combining independent and…

Methodology · Statistics 2021-09-08 Yusi Fang , George C. Tseng , Chung Chang

A random vector $X$ with representation $X=\sum_{j\geq0}A_jZ_j$ is considered. Here, $(Z_j)$ is a sequence of independent and identically distributed random vectors and $(A_j)$ is a sequence of random matrices, `predictable' with respect to…

Probability · Mathematics 2009-09-29 Henrik Hult , Gennady Samorodnitsky

The masses of data now available have opened up the prospect of discovering weak signals using machine-learning algorithms, with a view to predictive or interpretation tasks. As this survey of recent results attempts to show, bringing…

Statistics Theory · Mathematics 2026-05-06 Stephan Clémençon , Anne Sabourin

We study the long-time behavior of the scaled walker (particle) position associated with decoupled continuous-time random walk which is characterized by superheavy-tailed distribution of waiting times and asymmetric heavy-tailed…

Statistical Mechanics · Physics 2013-02-19 S. I. Denisov , Yu. S. Bystrik , H. Kantz

We study the empirical version of halfspace depths with the objective of establishing a connection between the rates of convergence and the tail behaviour of the corresponding underlying distributions. The intricate interplay between the…

Statistics Theory · Mathematics 2025-06-03 Sibsankar Singha , Marie Kratz , Sreekar Vadlamani

We consider the tail behavior of random variables $R$ which are solutions of the distributional equation $R\stackrel{d}{=}Q+MR$, where $(Q,M)$ is independent of $R$ and $|M|\le 1$. Goldie and Gr\"{u}bel showed that the tails of $R$ are no…

Probability · Mathematics 2010-02-08 Paweł Hitczenko , Jacek Wesołowski

We consider the tail distribution of the edge cover time of a specific non-Markov process, $\delta$ once-reinforced random walk, on finite connected graphs, whose transition probability is proportional to weights of edges. Here the weights…

Probability · Mathematics 2025-05-09 Xiangyu Huang , Yong Liu , Kainan Xiang

This paper addresses the advancement of probability tail bound analysis, a crucial statistical tool for assessing the probability of large deviations of random variables from their expected values. Traditional tail bounds, such as Markov's,…

Probability · Mathematics 2024-08-22 Shih-Yu Chang

We consider heavy-tailed distributions and compare the well-known estimators of the tail index, based on extreme value theory with a comparatively recent estimator based on a different idea.

Probability · Mathematics 2016-08-14 Vygantas Paulauskas , Marijus Vaičiulis

We introduce the Zeta Tail(a) probability distribution as a new model for random damage-event counts in risk analysis. Although readily motivated as an analogue of the Geometric(p) distribution, Zeta Tail(a) has received little attention in…

Methodology · Statistics 2025-07-09 Michael R. Powers

A probabilistic representation for a class of weighted $p$-radial distributions, based on mixtures of a weighted cone probability measure and a weighted uniform distribution on the Euclidean $\ell_p^n$-ball, is derived. Large deviation…

Probability · Mathematics 2022-06-01 Tom Kaufmann , Christoph Thaele

We present several refinements on the fluctuations of sequences of random vectors (with values in the Euclidean space $\mathbb{R}^d$) which converge after normalization to a multidimensional Gaussian distribution. More precisely we refine…

Probability · Mathematics 2022-03-04 Pierre-Loïc Méliot , Ashkan Nikeghbali

This article describes mathematical methods for estimating the top-tail of the wealth distribution and therefrom the share of total wealth that the richest $p$ percent hold, which is an intuitive measure of inequality. As the data base for…

Applications · Statistics 2018-07-11 Christoph Dalitz

Motivated by a bidimensional discrete-time risk model in insurance, we study the second-order asymptotics for two kinds of tail probabilities of the stochastic discounted value of aggregate net losses including two business lines. These are…

Probability · Mathematics 2025-01-22 Bingzhen Geng , Yang Liu , Shijie Wang

An infinite convergent sum of independent and identically distributed random variables discounted by a multiplicative random walk is called perpetuity, because of a possible actuarial application. We give three disjoint groups of sufficient…

Probability · Mathematics 2021-07-01 Dariusz Buraczewski , Piotr Dyszewski , Alexander Iksanov , Alexander Marynych

For purposes of Value-at-Risk estimation, we consider several multivariate families of heavy-tailed distributions, which can be seen as multidimensional versions of Paretian stable and Student's t distributions allowing different marginals…

Risk Management · Quantitative Finance 2011-12-20 Carlo Marinelli , Stefano d'Addona , Svetlozar T. Rachev

We obtain a number of new general properties, related to the closedness of the class of long-tailed distributions under convolutions, that are of interest themselves and may be applied in many models that deal with "plus" and/or "max"…

Probability · Mathematics 2015-11-24 Hui Xu , Sergey Foss , Yuebao Wang

The QQ plot is a commonly used technique for informally deciding whether a univariate random sample of size n comes from a specified distribution F. The QQ plot graphs the sample quantiles against the theoretical quantiles of F and then a…

Probability · Mathematics 2007-06-13 Bikramjit Das , Sidney I. Resnick

Ex ante forecast outcomes should be interpreted as counterfactuals (potential histories), with errors as the spread between outcomes. Reapplying measurements of uncertainty about the estimation errors of the estimation errors of an…

Risk Management · Quantitative Finance 2012-09-12 Nassim N. Taleb

We present sharp tail asymptotics for the density and the distribution function of linear combinations of correlated log-normal random variables, that is, exponentials of components of a correlated Gaussian vector. The asymptotic behavior…

Probability · Mathematics 2016-01-07 Archil Gulisashvili , Peter Tankov