Introduction

Extreme value theory has emerged as one of the most important statistical disciplines for the applied sciences over the last 50 years. Extreme value techniques are also becoming widely used in many other disciplines. For example: for portfolio adjustment in the insurance industry; for risk assessment on financial markets; and for traffic prediction in telecommunications. At the time of writing, in the past twelve months alone, applications of extreme value modeling have been published in the fields of alloy strength prediction (Tryon & Cruse, 2000); ocean wave modeling (Dawson, 2000); memory cell failure (McNulty et al., 2000); wind engineering (Harris, 2001); management strategy (Dahan & Mendelson, 2001); biomedical data processing (Roberts, 2000); thermodynamics of earthquakes (Lavenda & Cipollone, 2000); assessment of meteorological change (Thompson et al., 2001); non-linear beam vibrations (Dunne & Ghanbari, 2001); and food science (Kawas & Moreira, 2001).