Handbook of Statistics of Extremes (Chapman & Hall/crc Handbooks of Modern Statistical Methods)

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Handbook of Statistics of Extremes (Chapman & Hall/crc Handbooks of Modern Statistical Methods)

de Carvalho, Miguel (EDT)/ Huser, Raphaël (EDT)/ Naveau, Philippe (EDT)

ウェブストア価格 ¥55,264（本体¥50,240）
Chapman & Hall/CRC（2026/07発売）
外貨定価 US$ 250.00
ポイント 502pt

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製本 Hardcover:ハードカバー版／ページ数 800 p.
言語 ENG
商品コード 9781032519807

Full Description

Statistics of extremes is a prominent field of research concerned with modeling the risk of occurrence of extreme events, that is, low-probability-high-impact events such as a stock market crash, hurricanes, heatwaves, and widespread flooding.

The Handbook of Statistics of Extremes covers statistical models for univariate, multivariate, and spatio-temporal extreme values. Written by leading experts from around the world, it serves as a key reference for statisticians and data scientists, as well as for professionals working in risk modeling—such as geophysical and climate scientists, financial analysts, and health clinicians and neuroscientists—and as a valuable resource for practitioners and graduate students who wish to deepen their understanding of the statistical modeling of extreme events.

Key Features:

· Presents frequentist and Bayesian methods, as well as AI-based techniques for extreme value analysis.

· Details how to model the frequency, magnitude, and spatio-temporal dependence of extreme events, and how to extrapolate into the tails of a distribution beyond observed data.

· Provides code, data, and other additional materials available here: https://extremestats.github.io/Handbook/.

Editors Contributors Basic Symbols Part I Opening Remarks 1. Handbook Outline Part II Univariate Extremes 2. Modeling Univariate Extremes—Why and How 3. Learning About Extreme Value Distributions from Data 4. Bayesian Methods for Extreme Value Analysis 5. Jointly Modeling the Bulk and Tails 6. Regression Models for Extreme Events Part III Multivariate Extremes 7. Multivariate Extreme Value Theory 8. Measures of Extremal Dependence 9. Regression Models for Multivariate Extremes 10. Conditional Extremes Modeling 11. Principal Component Analysis for Multivariate Extremes 12. Clustering Methods for Multivariate Extremes 13. Graphical Models for Multivariate Extremes Part IV Spatial and Temporal Extremes 14. Time Series in Extremes 15. Max-Stable Processes for Spatial Extremes 16. Pareto Processes for Threshold Exceedances in Spatial Extremes 17. Subasymptotic Models for Spatial Extremes 18. Space-Time Modeling of Extremes Part V Emerging Topics 19. Causality and Extremes 20. On the Simulation of Extreme Events with Neural Networks 21. Extreme Quantile Regression with Deep Learning 22. Risk Measures Beyond Quantiles Part VI Applications and Case Studies 23. Detection and Attribution of Extreme Weather Events: A Statistical Review 24. Evaluation of Extreme Forecasts and Projections 25. Statistical Modeling of Extreme Precipitation 26. Statistics of Extremes for Wildfires 27. Statistics of Extremes for Landslides and Earthquakes 28. Tail Risk Analysis for Financial Time Series 29. Statistics of Extremes for the Insurance Industry 30. Statistics of Extremes for Neuroscience 31. Statistics of Extremes for Incomplete Data, with Application to Lifetime and Liability Claim Modeling Sources Index