| |
|
|
|
|
|
|
|
|
1. |
Record Nr. |
UNISA996418273703316 |
|
|
Autore |
Kulik Rafal |
|
|
Titolo |
Heavy-Tailed Time Series [[electronic resource] /] / by Rafal Kulik, Philippe Soulier |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
New York, NY : , : Springer New York : , : Imprint : Springer, , 2020 |
|
|
|
|
|
|
|
ISBN |
|
|
|
|
|
|
Edizione |
[1st ed. 2020.] |
|
|
|
|
|
Descrizione fisica |
|
1 online resource (XIX, 681 p. 7 illus., 5 illus. in color.) |
|
|
|
|
|
|
Collana |
|
Springer Series in Operations Research and Financial Engineering, , 1431-8598 |
|
|
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
Probabilities |
Statistics |
Applied mathematics |
Engineering mathematics |
Probability Theory and Stochastic Processes |
Statistical Theory and Methods |
Applications of Mathematics |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Nota di bibliografia |
|
Includes bibliographical references and index. |
|
|
|
|
|
|
Nota di contenuto |
|
Regular variation -- Regularly varying random variables -- Regularly varying random vectors -- Dealing with extremal independence -- Regular variation of series and random sums -- Regularly varying time series -- Limit theorems -- Convergence of clusters-. Point process convergence -- Convergence to stable and extremal processes -- The tall empirical and quantile processes -- Estimation of cluster functionals -- Estimation for extremally independent time series -- Bootstrap -- Time series models -- Max-stable processes -- Markov chains -- Moving averages -- Long memory processes -- Appendices. . |
|
|
|
|
|
|
|
|
Sommario/riassunto |
|
This book aims to present a comprehensive, self-contained, and concise overview of extreme value theory for time series, incorporating the latest research trends alongside classical methodology. Appropriate for graduate coursework or professional reference, the book requires a background in extreme value theory for i.i.d. data and basics of time series. Following a brief review of foundational concepts, it progresses linearly through topics in limit theorems and time series models while |
|
|
|
|
|
|
|
|
|
|
including historical insights at each chapter’s conclusion. Additionally, the book incorporates complete proofs and exercises with solutions as well as substantive reference lists and appendices, featuring a novel commentary on the theory of vague convergence. |
|
|
|
|
|
| |