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Full Description
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.
Contents
Univariate Extreme Value Analysis. Multivariate Extreme Value Analysis. Univariate Extreme Value Mixture Modeling. Threshold Selection in Extreme Value Analysis. Threshold Modeling of Nonstationary Extremes. Block-Maxima of Vines. Time Series of Extremes. Max-Autoregressive and Moving Maxima Models for Extremes. Spatial Extremes and Max-Stable Processes. Simulation of Max-Stable Processes. Conditional Simulation of Max-Stable Processes. Composite Likelihood for Extreme Values. Bayesian Inference for Extreme Value Modeling. Modeling Extremes Using Approximate Bayesian Computation. Estimation of Extreme Conditional Quantiles. Extreme Dependence Models. Nonparametric Estimation of Extremal Dependence. An Overview of Nonparametric Tests of Extreme-Value Dependence and of Some Related Statistical Procedures. Extreme Risks of Financial Investments. Interplay of Insurance and Financial Risks with Bivariate Regular Variation. Weather and Climate Disasters. The Analysis of Safety Data from Clinical Trials. Analysis of Bivariate Survival Data Based on Copulas with Log Generalized Extreme Value Marginals. Change Point Analysis of Top Batting Average. Computing Software.
