Extreme Value Modeling and Risk Analysis: Methods and Applications presents a broad overview of statistical modeling of extreme events along with the most recent methodologies and various applications. The book brings together background material and advanced topics, eliminating the need to sort through the massive amount of literature on the subject. After reviewing univariate extreme value analysis and multivariate extremes, the book explains univariate extreme value mixture modeling, threshold selection in extreme value analysis, and threshold modeling of non-stationary extremes. It presents new results for block-maxima of vine copulas, develops time series of extremes with applications from climatology, describes max-autoregressive and moving maxima models for extremes, and discusses spatial extremes and max-stable processes. The book then covers simulation and conditional simulation of max-stable processes; inference methodologies, such as composite likelihood, Bayesian inference, and approximate Bayesian computation; and inferences about extreme quantiles and extreme dependence. It also explores novel applications of extreme value modeling, including financial investments, insurance and financial risk management, weather and climate disasters, clinical trials, and sports statistics. Risk analyses related to extreme events require the combined expertise of statisticians and domain experts in climatology, hydrology, finance, insurance, sports, and other fields. This book connects statistical/mathematical research with critical decision and risk assessment/management applications to stimulate more collaboration between these statisticians and specialists.
Univariate Extreme Value Analysis Dipak Dey, Dooti Roy, and Jun Yan Multivariate Extreme Value Analysis Dipak Dey, Yujing Jiang, and Jun Yan Univariate Extreme Value Mixture Modeling Carl Scarrott Threshold Selection in Extreme Value Analysis Frederico Caeiro and M. Ivette Gomes Threshold Modeling of Nonstationary Extremes Paul J. Northrop, Philip Jonathan, and David Randell Block-Maxima of Vines Matthias Killiches and Claudia Czado Time Series of Extremes Brian J. Reich and Benjamin A. Shaby Max-Autoregressive and Moving Maxima Models for Extremes Zhengjun Zhang, Liang Peng, and Timothy Idowu Spatial Extremes and Max-Stable Processes Mathieu Ribatet, Clement Dombry, and Marco Oesting Simulation of Max-Stable Processes Marco Oesting, Mathieu Ribatet, and Clement Dombry Conditional Simulation of Max-Stable Processes Clement Dombry, Marco Oesting, and Mathieu Ribatet Composite Likelihood for Extreme Values Huiyan Sang Bayesian Inference for Extreme Value Modeling Alec Stephenson Modeling Extremes Using Approximate Bayesian Computation Robert Erhardt and Scott A. Sisson Estimation of Extreme Conditional Quantiles Huixia Judy Wang and Deyuan Li Extreme Dependence Models Boris Beranger and Simone Padoan Nonparametric Estimation of Extremal Dependence Anna Kiriliouk, Johan Segers, and Michal Warchol An Overview of Nonparametric Tests of Extreme-Value Dependence and of Some Related Statistical Procedures Axel Bucher and Ivan Kojadinovic Extreme Risks of Financial Investments Ye Liu and Jonathan A. Tawn Interplay of Insurance and Financial Risks with Bivariate Regular Variation Qihe Tang and Zhongyi Yuan Weather and Climate Disasters Richard W. Katz The Analysis of Safety Data from Clinical Trials Ioannis Papastathopoulos and Harry Southworth Analysis of Bivariate Survival Data Based on Copulas with Log Generalized Extreme Value Marginals Dooti Roy, Vivekananda Roy, and Dipak Dey Change Point Analysis of Top Batting Average Sy Han Chiou, Sangwook Kang, and Jun Yan Computing Software Eric Gilleland
