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Extremes
Extremes

Published/Hosted by Springer. ISSN (printed): 1386-1999. ISSN (electronic): 1572-915X.

Extremes publishes original research on all aspects of statistical extreme value theory and its applications in science engineering economics and other fields. Authoritative and timely reviews of theoretical advances and of extreme value methods and problems in important applied areas including detailed case studies are welcome and will be a regular feature. All papers are refereed. Publication will be swift: in particular electronic submission and correspondence is encouraged. Statistical extreme value methods encompass a very wide range of problems: Extreme waves rainfall and floods are of basic importance in oceanography and hydrology as are high windspeeds and extreme temperatures in meteorology and catastrophic claims in insurance. The waveforms and extremes of random loads determine lifelengths in structural safety corrosion and metal fatigue. High concentrations of pollutants constitute health hazards. Large fluctuations in asset share and bond prices and in exchange and interest rates have serious consequences for the economy. Much of risk and reliability theory is concerned with extreme occurrences. Methods and problems in tail estimation statistical process control sequential analysis and heavy-tailed models for time series are closely related to extreme value theory. Numerical methods optimization simulation and resampling are of interest for statistical extremes. Publication of research on statistical extremes is very scattered: e.g. in probability journals like the Annals of Probability or the Applied Probability journals in statistical journals such as the Annals of Statistics the Journals of the Royal Statistical Society or Technometrics and in journals in hydrology oceanography meteorology reliability civil engineering economics finance and physics. The fragmented publication leads to long delays before theoretical advances find their way into practical application. Similarly important applied problems are slow to gain attention by theoreticians. The aim of Extremes is to advance and speed up research and applications by providing a unified forum for the best papers on statistical extremes. In Extremes applied scientists will find comprehensive and up-to-date coverage of theoretical developments specialists will find authoritative discussions of urgent applied problems and authors will find the best medium for the dissemination and use of their results.

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