Extreme value modeling and risk analysis: methods and applications - Boca Raton CRC Press 2016 - xx, 520 p.

Table of Contents:

1 Univariate Extreme Value Analysis
2 Multivariate Extreme Value Analysis
3 Univariate Extreme Value Mixture Modeling
4 Threshold Selection in Extreme Value Analysis
5 Threshold Modeling of Nonstationary Extremes
6 Block-Maxima of Vines
7 Time Series of Extremes
8 Max-Autoregressive and Moving Maxima Models for Extremes
9 Spatial Extremes and Max-Stable Processes
10 Simulation of Max-Stable Processes
11 Conditional Simulation of Max-Stable Processes
12 Composite Likelihood for Extreme Values
13 Bayesian Inference for Extreme Value Modeling
14 Modeling Extremes Using Approximate Bayesian Computation
15 Estimation of Extreme Conditional Quantiles
16 Extreme Dependence Models
17 Nonparametric Estimation of Extremal Dependence
18 An Overview of Nonparametric Tests of Extreme-Value Dependence and of Some Related Statistical Procedures
19 Extreme Risks of Financial Investments
20 Interplay of Insurance and Financial Risks with Bivariate Regular Variation
21 Weather and Climate Disasters
22 The Analysis of Safety Data from Clinical Trials
23 Analysis of Bivariate Survival Data Based on Copulas with Log Generalized Extreme Value Marginals
24 Change Point Analysis of Top Batting Average
25 Computing Software

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.



Extreme Value Theory
Risk Assessment
Mathematical Models

519.2 / E9

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