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Extreme Value Theory in Engineering

After several years of work with engineers in the area of extremes, several Ph. D. Theses of my students on this topic and the contact, personal or through their many publications, with mathematicians and statisticians, I discovered the lack of close communication and collaboration between practitioners and theorists. This fact is the main cause, on the one hand, for engineers to be unaware of the very many recent advances in the area of extremes, and, on the other hand, for the mathematicians and statisticians to find practical applications and motivations for their theoretical work. The exponentially increasing number of publications on any subject makes it impossible to become a specialist in a wide area of knowledge. Thus, the need for collaboration and joint work. All this has increased my motivation for writing the present book and clearly defined its goal. However, to be a bridge between engineers and mathematicians or statisticians is not an easy task, as experience demonstrates; their daily languages and main concerns are far enough apart to make it difficult. In addition, everything must be done at the risk of being criticized from bothsides. In this context, the present book will be only a grain of sand in a beach still to be built.





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Extreme Values in Finance,Telecommunications,and the Environment


The first chapter, written by Richard Smith, gives a survey of how this paradigm answers a variety of questions of interest to an applied scientist in climatology, in-surance, and finance. The chapter also reviews parts of univariate extreme value theory and discusses estimation, diagnostics, multivariate extremes, and max-stable processes.



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Statistical Analysis of Extreme Values


First of all we would like to thank all those who showed a steady, extraordinary in-terest in this book about extreme value analysis. This gave the motivation, courage and opportunity to provide an update of the book and to work out new topics, which primarily focus on dependencies, conditional analysis based on serial and covariate information, predictions, and the multivariate modeling of extremes.


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Studies in Theoretical and Applied Statistics(Sringer)




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