Directly oriented towards real practical application, this book develops both the basic theoretical framework of extreme value models and the statistical inferential techniques for using these models in practice. Intended for statisticians and non-statisticians alike, the theoretical treatment is el
An Introduction to Statistical Modeling of Extreme Values
β Scribed by Coles S.
- Publisher
- Springer
- Year
- 2001
- Tongue
- English
- Leaves
- 221
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
Directly oriented towards real practical application, this book develops both the basic theoretical framework of extreme value models and the statistical inferential techniques for using these models in practice. Intended for statisticians and non-statisticians alike, the theoretical treatment is elementary, with heuristics often replacing detailed mathematical proof. Most aspects of extreme modeling techniques are covered, including historical techniques (still widely used) and contemporary techniques based on point process models. A wide range of worked examples, using genuine datasets, illustrate the various modeling procedures and a concluding chapter provides a brief introduction to a number of more advanced topics, including Bayesian inference and spatial extremes. All the computations are carried out using S-PLUS, and the corresponding datasets and functions are available via the Internet for readers to recreate examples for themselves. An essential reference for students and researchers in statistics and disciplines such as engineering, finance and environmental science, this book will also appeal to practitioners looking for practical help in solving real problems. Stuart Coles is Reader in Statistics at the University of Bristol, UK, having previously lectured at the universities of Nottingham and Lancaster. In 1992 he was the first recipient of the Royal Statistical Society's research prize. He has published widely in the statistical literature, principally in the area of extreme value modeling.
β¦ Table of Contents
Cover\r......Page 1
Title Page\r......Page 2
Preface\r......Page 6
Contents\r......Page 10
Ch 1. Introduction\r......Page 14
Ch 2. Basics of Statistical Modeling\r......Page 31
Ch 3. Classical Extreme Value Theory and Models\r......Page 58
Ch 4. Threshold Models\r......Page 87
Ch 5. Extremes of Dependent Sequences\r......Page 105
Ch 6. Extremes of Non-stationary Sequences\r......Page 118
Ch 7. A Point Process Characterization of Extremes\r......Page 137
Ch 8. Multivariate Extremes\r......Page 155
Ch 9. Further Topics\r......Page 182
Appendix A\r......Page 198
References\r......Page 208
Index\r......Page 218
β¦ Subjects
ΠΠΈΠ±Π»ΠΈΠΎΡΠ΅ΠΊΠ°;ΠΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½Π°Ρ Π»ΠΈΡΠ΅ΡΠ°ΡΡΡΠ°;R;
π SIMILAR VOLUMES
<p>Directly oriented towards real practical application, this book develops both the basic theoretical framework of extreme value models and the statistical inferential techniques for using these models in practice. Intended for statisticians and non-statisticians alike, the theoretical treatment is
Extreme Value Theory offers a careful, coherent exposition of the subject starting from the probabilistic and mathematical foundations and proceeding to the statistical theory. The book covers both the classical one-dimensional case as well as finite- and infinite-dimensional settings. All the main
<span>Part of The SAGE Quantitative Research Kit, this text helps you make the crucial steps towards mastering multivariate analysis of social science data, introducing the fundamental linear and non-linear regression models used in quantitative research. Peter Martin covers both the theory and appl