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There is an increasing interest to understand the dependence structure of a random vector not only in the center of its distribution but also in the tails. Extreme-value theory tackles the problem of modelling the joint tail of a…

Methodology · Statistics 2014-11-04 Anna Kiriliouk , Johan Segers , Michal Warchol

Our contribution is to widen the scope of extreme value analysis applied to discrete-valued data. Extreme values of a random variable $X$ are commonly modeled using the generalized Pareto distribution, a method that often gives good results…

Statistics Theory · Mathematics 2017-07-18 Adrien Hitz , Richard Davis , Gennady Samorodnitsky

In this paper, we study the perturbation of the extreme singular values of a matrix in the particular case where it is obtained after appending an arbitrary column vector. Such results have many applications in bifurcation theory, signal…

Spectral Theory · Mathematics 2014-12-17 Stephane Chretien , Sebastien Darses

We study the distribution of maxima (Extreme Value Statistics) for sequences of observables computed along orbits generated by random transformations. The underlying, deterministic, dynamical system can be regular or chaotic. In the former…

Dynamical Systems · Mathematics 2015-06-11 Davide Faranda , Jorge Milhazes Freitas , Valerio Lucarini , Giorgio Turchetti , Sandro Vaienti

Whether an extreme observation is an outlier or not, depends strongly on the corresponding tail behaviour of the underlying distribution. We develop an automatic, data-driven method to identify extreme tail behaviour that deviates from the…

Methodology · Statistics 2019-12-06 Shrijita Bhattacharya , Jan Beirlant

We investigate extreme value theory of a class of random sequences defined by the all-time suprema of aggregated self-similar Gaussian processes with trend. This study is motivated by its potential applications in various areas and its…

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

Multivariate extreme value statistical analysis is concerned with observations on several variables which are thought to possess some degree of tail-dependence. In areas such as the modeling of financial and insurance risks, or as the…

Applications · Statistics 2014-12-31 Alexis Bienvenüe , Christian Y. Robert

Preferential attachment is an appealing edge generating mechanism for modeling social networks. It provides both an intuitive description of network growth and an explanation for the observed power laws in degree distributions. However,…

Methodology · Statistics 2017-12-21 Phyllis Wan , Tiandong Wang , Richard A. Davis , Sidney I. Resnick

This paper introduces a novel approach employing extreme value theory to analyze queue lengths within a corridor controlled by adaptive controllers. We consider the maximum queue lengths of a signalized corridor consisting of nine…

Systems and Control · Electrical Eng. & Systems 2024-08-05 Shakib Mustavee , Pushkin Kachroo , Shaurya Agarwal

Maximum likelihood estimations for the parameters of extreme value distributions are discussed in this paper using fixed point iteration. The commonly used numerical approach for addressing this problem is the Newton-Raphson approach which…

Computation · Statistics 2009-02-03 Tewfik Kernane , Zohrh A. Raizah

Statistical extreme value theory is concerned with the use of asymptotically motivated models to describe the extreme values of a process. A number of commonly used models are valid for observed data that exceed some high threshold.…

Methodology · Statistics 2014-12-10 J. Lee , Y. Fan , S. A. Sisson

The extremal index is a quantity introduced in extreme value theory to measure the presence of clusters of exceedances. In the dynamical systems framework, it provides important information about the dynamics of the underlying systems. In…

Dynamical Systems · Mathematics 2020-01-08 Th. Caby , D. Faranda , S. Vaienti , P. Yiou

Causal effect estimation seeks to determine the impact of an intervention from observational data. However, the existing causal inference literature primarily addresses treatment effects on frequently occurring events. But what if we are…

Machine Learning · Statistics 2025-06-18 Jiyuan Tan , Jose Blanchet , Vasilis Syrgkanis

Detecting anomalies in a temporal sequence of graphs can be applied is areas such as the detection of accidents in transport networks and cyber attacks in computer networks. Existing methods for detecting abnormal graphs can suffer from…

Machine Learning · Computer Science 2025-02-03 Sevvandi Kandanaarachchi , Conrad Sanderson , Rob J. Hyndman

This study provides a summary of the theory which enables the analysis of extreme values, i.e., of measurements acquired from the observation of extraordinary/rare physical phenomena. The formalism is developed in a transparent way,…

Data Analysis, Statistics and Probability · Physics 2024-07-02 Evangelos Matsinos

In a wide variety of situations, anomalies in the behaviour of a complex system, whose health is monitored through the observation of a random vector X = (X1,. .. , X d) valued in R d , correspond to the simultaneous occurrence of extreme…

Methodology · Statistics 2019-07-18 Maël Chiapino , Stéphan Clémençon , Vincent Feuillard , Anne Sabourin

This note presents a rather intuitive approach to extreme value theory. This approach was devised mostly for pedagogical reason.

Statistics Theory · Mathematics 2008-11-06 Philippe Barbe

This paper investigates the use of extreme value theory for modelling the distribution of demand-net-of-wind for capacity adequacy assessment. Extreme value theory approaches are well-established and mathematically justified methods for…

Applications · Statistics 2019-07-31 Amy L Wilson , Stan Zachary

Motivated by the psychological literature on the "peak-end rule" for remembered experience, we perform an analysis within a random walk framework of a discrete choice model where agents' future choices depend on the peak memory of their…

Statistical Mechanics · Physics 2015-06-01 Rosemary J. Harris

We study distributional robustness in the context of Extreme Value Theory (EVT). We provide a data-driven method for estimating extreme quantiles in a manner that is robust against incorrect model assumptions underlying the application of…

Statistics Theory · Mathematics 2020-06-09 Jose Blanchet , Fei He , Karthyek R. A. Murthy