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Preface to the Third Edition | p. v |
Preface to the Second Edition | p. vii |
Preface to the First Edition | p. ix |
The IID Case: Functional Laws of Small Numbers | p. 1 |
Functional Laws of Small Numbers | p. 3 |
Introduction | p. 3 |
Bounds for the Functional Laws of Small Numbers | p. 7 |
Applications | p. 14 |
Extreme Value Theory | p. 25 |
Domains of Attraction, von Mises Conditions | p. 25 |
The ¿-Neighborhood of a GPD | p. 35 |
The Peaks-Over-Threshold Method | p. 42 |
Parameter Estimation in ¿-Neighborhoods of GPD | p. 46 |
Initial Estimation of the Class Index | p. 55 |
Power Normalization and p-Max Stable Laws | p. 65 |
Heavy and Super-Heavy Tail Analysis | p. 75 |
Estimation of Conditional Curves | p. 103 |
Poisson Process Approach | p. 103 |
Applications: The Non-parametric Case | p. 111 |
Applications: The Semiparametric Case | p. 114 |
Extension to Several Points | p. 120 |
A Nearest Neighbor Alternative | p. 124 |
Application: Optimal Accuracy of Estimators | p. 128 |
The IID Case: Multivariate Extremes | p. 133 |
Basic Theory of Multivariate Maxima | p. 135 |
Limiting Distributions of Multivariate Maxima | p. 135 |
Representations and Dependence Functions | p. 140 |
Pickands Representation and Dependence Function | p. 147 |
The D-Norm | p. 157 |
Multivariate Generalized Pareto Distributions | p. 171 |
The Basics | p. 171 |
Multivariate Peaks-Over-Threshold Approach | p. 177 |
Peaks-Over-Threshold Stability of a GPD | p. 190 |
A Spectral Decomposition Based on Pickands Coordinates | p. 194 |
Multivariate Domains of Attraction, Spectral Neighborhoods | p. 201 |
The Pickands Transform | p. 209 |
Simulation Techniques | p. 221 |
Testing the GPD Assumption, Threshold Selection | p. 229 |
Parametric Estimation Procedures | p. 240 |
Testing in Logistic GPD Models | p. 250 |
The Pickands Approach in the Bivariate Case | p. 259 |
Preliminaries | p. 259 |
The Measure Generating Function M | p. 267 |
The Pickands Transform in the Bivariate Case | p. 272 |
The Tail Dependence Function | p. 280 |
Testing Tail Dependence against Residual Tail Dependence | p. 288 |
Estimation of the Angular Density in Bivariate GP Models | p. 299 |
Multivariate Extremes: Supplementary Concepts and Results | p. 311 |
Strong Approximation of Exceedances | p. 311 |
Further Concepts of Extremes | p. 317 |
Thinned Empirical Processes | p. 320 |
Max-Stable Stochastic Processes | p. 335 |
Non-IID Observations | p. 341 |
Introduction to the Non-IID Case | p. 343 |
Definitions | p. 343 |
Stationary Random Sequences | p. 344 |
Independent Random Sequences | p. 346 |
Non-stationary Random Sequences | p. 351 |
Triangular Arrays of Discrete Random Variables | p. 352 |
Extremes of Random Sequences | p. 357 |
Introduction and General Theory | p. 357 |
Applications: Stationary Sequences | p. 368 |
Applications: Independent Sequences | p. 372 |
Applications: Non-stationary Sequences | p. 374 |
Extensions: Random Fields | p. 379 |
Extremes of Gaussian Processes | p. 381 |
Introduction | p. 381 |
Stationary Gaussian Processes | p. 382 |
Non-stationary Gaussian Processes | p. 388 |
Application: Empirical Characteristic Functions | p. 414 |
Extensions: Maxima of Gaussian fields | p. 416 |
Extensions for Rare Events | p. 419 |
Rare Events of Random Sequences | p. 419 |
The Point Process of Exceedances | p. 423 |
Application to Peaks-over-Threshold | p. 428 |
Application to Rare Events | p. 431 |
Triangular Arrays of Rare Events | p. 439 |
Multivariate Extremes of Non-IID Sequences | p. 447 |
Statistics of Extremes | p. 455 |
Introduction | p. 455 |
Estimation of ¿ and ¿( ·) | p. 456 |
Application to Ecological Data | p. 458 |
Frost Data: An Application | p. 462 |
Author Index | p. 473 |
Subject Index | p. 477 |
Bibliography | p. 483 |
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