Heavy-tailed time series / Rafal Kulik, Philippe Soulier.

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Bibliographic Details
Main Author: Kulik, Rafal
Other Authors: Soulier, Philippe, Prof
Format: eBook
Language:English
Published: New York, NY : Springer, 2020.
Series:Springer series in operations research.
Subjects:
Online Access:Click for online access

MARC

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100 1 |a Kulik, Rafal. 
245 1 0 |a Heavy-tailed time series /  |c Rafal Kulik, Philippe Soulier. 
260 |a New York, NY :  |b Springer,  |c 2020. 
300 |a 1 online resource (677 pages) 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Springer Series in Operations Research and Financial Engineering 
504 |a Includes bibliographical references and index. 
588 0 |a Print version record. 
505 0 |a 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. 
520 |a 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 chapters 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. 
650 0 |a Extreme value theory. 
650 0 |a Time-series analysis. 
650 7 |a Probability & statistics.  |2 bicssc 
650 7 |a Applied mathematics.  |2 bicssc 
650 7 |a Mathematics  |x Probability & Statistics  |x General.  |2 bisacsh 
650 7 |a Mathematics  |x Applied.  |2 bisacsh 
650 7 |a Matemáticas  |x Estadística aplicada  |2 embne 
650 0 7 |a Estadística aplicada  |2 embucm 
650 7 |a Extreme value theory  |2 fast 
650 7 |a Time-series analysis  |2 fast 
700 1 |a Soulier, Philippe,  |c Prof.  |1 https://id.oclc.org/worldcat/entity/E39PCjG8tCgXkPCwddMfKKVvd3 
758 |i has work:  |a Heavy-tailed time series (Text)  |1 https://id.oclc.org/worldcat/entity/E39PCGD89MjptkXYp4tJjf9yMP  |4 https://id.oclc.org/worldcat/ontology/hasWork 
776 0 8 |i Print version:  |a Kulik, Rafal.  |t Heavy-Tailed Time Series.  |d New York, NY : Springer, ©2020  |z 9781071607350 
830 0 |a Springer series in operations research. 
856 4 0 |u https://holycross.idm.oclc.org/login?auth=cas&url=https://link.springer.com/10.1007/978-1-0716-0737-4  |y Click for online access 
903 |a SPRING-MATH2020 
994 |a 92  |b HCD