Titlebook: Applied Extreme Value Statistics; With a Special Focus Arvid Naess Book 2024 The Editor(s) (if applicable) and The Author(s), under exclusi

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https://doi.org/10.1007/978-3-658-27793-2e structures. Over the years several reports had been filed detailing damage of the deck structure of offshore platforms due to wave impacts. In fact, such damage seemed to occur more frequently than could be expected from predictions based on standard theory. These wave impacts are highly undesirab

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https://doi.org/10.1007/978-3-658-27793-2k of flooding for a given location. This risk is typically expressed as the flooding levels associated with various return periods, e.g., the 100 year flooding level. In Norway the concerns about flooding events are primarily connected with two types of flooding: On the one hand, in rivers and lakes

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Arvid NaessEnables the reader to carry out accurate extreme value estimation without having to assume asymptotic distributions.Since real life data are never asymptotic, methods are presented that avoid making t

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https://doi.org/10.1007/978-3-031-60769-1Extreme Value Statistics; Monte Carlo Methods; ACER Method; Space-Time Extremes; Asymptotic Extreme Valu

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978-3-031-60771-4The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

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How to Earn a Seat at the Executive Table,. This has really opened the door for the use of Monte Carlo-based methods for solving a wide array of stochastic engineering problems. In this chapter the focus is on adapting Monte Carlo methods for estimation of extreme values of stochastic processes encountered in various engineering disciplines.

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Classical Extreme Value Theory,pe I, Type II, and Type III, in the same order. Important contributions to this theory were later made by Gnedenko (Ann Math 44:423–453, 1943), Gumbel (.. New York, NY: Columbia University Press, 1958), and de Haan (On regular variation and its applications to the weak convergence of sample extremes. Tract, Mathematical Centre, Amsterdam, 1970).

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Monte Carlo Methods and Extreme Value Estimation,. This has really opened the door for the use of Monte Carlo-based methods for solving a wide array of stochastic engineering problems. In this chapter the focus is on adapting Monte Carlo methods for estimation of extreme values of stochastic processes encountered in various engineering disciplines.