Laws of Small Numbers

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Edition: 3rd
Format: Paperback
Pub. Date: 2010-10-29
Publisher(s): Birkhauser
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Summary

Since the publication of the first edition of this seminar book in 1994, the theory and applications of extremes and rare events have enjoyed an enormous and still increasing interest. The intention of the book is to give a mathematically oriented development of the theory of rare events underlying various applications. This characteristic of the book was strengthened in the second edition by incorporating various new results. In this third edition, the dramatic change of focus of extreme value theory has been taken into account: from concentrating on maxima of observations it has shifted to large observations, defined as exceedances over high thresholds. One emphasis of the present third edition lies on multivariate generalized Pareto distributions, their representations, properties such as their peaks-over-threshold stability, simulation, testing and estimation.Reviews of the 2nd edition:"In brief, it is clear that this will surely be a valuable resource for anyone involved in, or seeking to master, the more mathematical features of this field."David Stirzaker, Bulletin of the London Mathematical Society"Laws of Small Numbers can be highly recommended to everyone who is looking for a smooth introduction to Poisson approximations in EVT and other fields of probability theory and statistics. In particular, it offers an interesting view on multivariate EVT and on EVT for non-iid observations, which is not presented in a similar way in any other textbook."Holger Drees, Metrika

Table of Contents

Preface to the Third Editionp. v
Preface to the Second Editionp. vii
Preface to the First Editionp. ix
The IID Case: Functional Laws of Small Numbersp. 1
Functional Laws of Small Numbersp. 3
Introductionp. 3
Bounds for the Functional Laws of Small Numbersp. 7
Applicationsp. 14
Extreme Value Theoryp. 25
Domains of Attraction, von Mises Conditionsp. 25
The ¿-Neighborhood of a GPDp. 35
The Peaks-Over-Threshold Methodp. 42
Parameter Estimation in ¿-Neighborhoods of GPDp. 46
Initial Estimation of the Class Indexp. 55
Power Normalization and p-Max Stable Lawsp. 65
Heavy and Super-Heavy Tail Analysisp. 75
Estimation of Conditional Curvesp. 103
Poisson Process Approachp. 103
Applications: The Non-parametric Casep. 111
Applications: The Semiparametric Casep. 114
Extension to Several Pointsp. 120
A Nearest Neighbor Alternativep. 124
Application: Optimal Accuracy of Estimatorsp. 128
The IID Case: Multivariate Extremesp. 133
Basic Theory of Multivariate Maximap. 135
Limiting Distributions of Multivariate Maximap. 135
Representations and Dependence Functionsp. 140
Pickands Representation and Dependence Functionp. 147
The D-Normp. 157
Multivariate Generalized Pareto Distributionsp. 171
The Basicsp. 171
Multivariate Peaks-Over-Threshold Approachp. 177
Peaks-Over-Threshold Stability of a GPDp. 190
A Spectral Decomposition Based on Pickands Coordinatesp. 194
Multivariate Domains of Attraction, Spectral Neighborhoodsp. 201
The Pickands Transformp. 209
Simulation Techniquesp. 221
Testing the GPD Assumption, Threshold Selectionp. 229
Parametric Estimation Proceduresp. 240
Testing in Logistic GPD Modelsp. 250
The Pickands Approach in the Bivariate Casep. 259
Preliminariesp. 259
The Measure Generating Function Mp. 267
The Pickands Transform in the Bivariate Casep. 272
The Tail Dependence Functionp. 280
Testing Tail Dependence against Residual Tail Dependencep. 288
Estimation of the Angular Density in Bivariate GP Modelsp. 299
Multivariate Extremes: Supplementary Concepts and Resultsp. 311
Strong Approximation of Exceedancesp. 311
Further Concepts of Extremesp. 317
Thinned Empirical Processesp. 320
Max-Stable Stochastic Processesp. 335
Non-IID Observationsp. 341
Introduction to the Non-IID Casep. 343
Definitionsp. 343
Stationary Random Sequencesp. 344
Independent Random Sequencesp. 346
Non-stationary Random Sequencesp. 351
Triangular Arrays of Discrete Random Variablesp. 352
Extremes of Random Sequencesp. 357
Introduction and General Theoryp. 357
Applications: Stationary Sequencesp. 368
Applications: Independent Sequencesp. 372
Applications: Non-stationary Sequencesp. 374
Extensions: Random Fieldsp. 379
Extremes of Gaussian Processesp. 381
Introductionp. 381
Stationary Gaussian Processesp. 382
Non-stationary Gaussian Processesp. 388
Application: Empirical Characteristic Functionsp. 414
Extensions: Maxima of Gaussian fieldsp. 416
Extensions for Rare Eventsp. 419
Rare Events of Random Sequencesp. 419
The Point Process of Exceedancesp. 423
Application to Peaks-over-Thresholdp. 428
Application to Rare Eventsp. 431
Triangular Arrays of Rare Eventsp. 439
Multivariate Extremes of Non-IID Sequencesp. 447
Statistics of Extremesp. 455
Introductionp. 455
Estimation of ¿ and ¿( ·)p. 456
Application to Ecological Datap. 458
Frost Data: An Applicationp. 462
Author Indexp. 473
Subject Indexp. 477
Bibliographyp. 483
Table of Contents provided by Ingram. All Rights Reserved.

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