Extreme Value Modeling and Risk Analysis

Methods and Applications
Herausgeber: Dey, Dipak K; Yan, Jun

• Gebundenes Buch

Produktbeschreibung

This book presents a broad overview of statistical modeling of extreme events along with the most recent methodologies and various applications. It brings together background material and advanced topics, eliminating the need to sort through the massive amount of literature on the subject. The book connects statistical/mathematical research with critical decision and risk assessment/management applications. It explores novel applications of extreme value modeling, including financial investments, climate disasters, clinical trials, and sports. Computer code is available on the editors' website.

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Produktdetails

• Verlag: CRC Press
• Seitenzahl: 540
• Erscheinungstermin: 21. Dezember 2015
• Englisch
• Abmessung: 241mm x 161mm x 38mm
• Gewicht: 934g
• ISBN-13: 9781498701297
• ISBN-10: 1498701299
• Artikelnr.: 42796729

Autorenporträt

Jun Yan is a professor in the Department of Statistics at the University of Connecticut. He was previously an assistant professor at the University of Iowa. He received a Ph.D. in statistics from the University of Wisconsin-Madison. His research interests include spatial extremes, copulas, survival analysis, estimating equations, clustered data analysis, statistical computing, and applications in public health and environment. Dipak K. Dey is a Board of Trustees Distinguished Professor in the Department of Statistics and associate dean of the College of Liberal Arts and Sciences at the University of Connecticut. He is an elected fellow of the International Society for Bayesian Analysis and American Association for the Advancement of Science, an elected member of the Connecticut Academy of Arts and Sciences and International Statistical Institute, and a fellow of the American Statistical Association and Institute of Mathematical Statistics. Dr. Dey is a co-editor and co-author of several books, including the Chapman & Hall/CRC Bayesian Modeling in Bioinformatics and A First Course in Linear Model Theory. His research interests include Bayesian analysis, bioinformatics, biostatistics, computational statistics, decision theory, environmental statistics, multivariate analysis, optics, reliability and survival analysis, statistical shape analysis, and statistical genetics.

Inhaltsangabe

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.