## Extreme value theory: proceedings of a conference held in Oberwolfach, Dec. 6-12, 1987The theory of extreme values has become a broad subject which is difficult to cover by a few authors. It is the purpose of this book to lay out in an expository way the broad spectrum of extremes by contributions, some of which are reviewing recent developments and some are including original ideas and results. In the last years, the complexity of problems and their tractability by mathematical methods stimulated a rapid development of mathematical theory that substantially helped to improve our understanding of extreme behavior. Due to the depth and richness of mathematical ideas, extreme value theory has become more and more interesting to mathematically oriented research workers. This was one of the reasons a conference on extreme value theory was held at the Mathematische Forschungsinstitut at Oberwolfach (FRG) in December 1987. The book is split into three parts with a total number of nine sections. The topics covered include probabilistic theory, statistical theory of extreme values, and multivariate extremes and records. |

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assume assumption asymptotic expansion asymptotically equal bivariate bounds characterization cluster consider constant convergence Corollary defined definition Deheuvels denote density dependence function distribution function domain of attraction ergodic estimator exists exponential distribution exponential family extremal index extremal processes extreme order statistics extreme value distribution extreme value theory finite Gaussian processes given Gumbel Hausdorff dimension Hence holds implies independent integral inter-record interval Leadbetter Lemma lim inf lim sup limiting distribution log.n loglogt margins Markov Math Mathematics maxima maximum obtain order statistics parameter Pickands point process Poisson process Prob probability proof of Theorem properties quantile quantile function random measure random variables record values regression regularly varying functions Reiss Resnick RFC—amplitude sample satisfies self-similar Slepian model process slowly varying stationary strong approximation Tiago de Oliveira wavelength and amplitude Wiener process zero