Overview
- Authors:
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M. R. Leadbetter
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Department of Statistics, The University of North Carolina, Chapel Hill, USA
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Georg Lindgren
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Department of Mathematical Statistics, University of Lund, Lund, Sweden
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Holger Rootzén
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Institute of Mathematical Statistics, University of Copenhagen, Copenhagen ø, Denmark
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Table of contents (15 chapters)
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Back Matter
Pages 305-336
About this book
Classical Extreme Value Theory-the asymptotic distributional theory for maxima of independent, identically distributed random variables-may be regarded as roughly half a century old, even though its roots reach further back into mathematical antiquity. During this period of time it has found significant application-exemplified best perhaps by the book Statistics of Extremes by E. J. Gumbel-as well as a rather complete theoretical development. More recently, beginning with the work of G. S. Watson, S. M. Berman, R. M. Loynes, and H. Cramer, there has been a developing interest in the extension of the theory to include, first, dependent sequences and then continuous parameter stationary processes. The early activity proceeded in two directions-the extension of general theory to certain dependent sequences (e.g., Watson and Loynes), and the beginning of a detailed theory for stationary sequences (Berman) and continuous parameter processes (Cramer) in the normal case. In recent years both lines of development have been actively pursued.
Authors and Affiliations
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Department of Statistics, The University of North Carolina, Chapel Hill, USA
M. R. Leadbetter
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Department of Mathematical Statistics, University of Lund, Lund, Sweden
Georg Lindgren
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Institute of Mathematical Statistics, University of Copenhagen, Copenhagen ø, Denmark
Holger Rootzén