Coverart for item
The Resource Heavy-Tailed Time Series, by Rafal Kulik, Philippe Soulier, (electronic resource)

Heavy-Tailed Time Series, by Rafal Kulik, Philippe Soulier, (electronic resource)

Label
Heavy-Tailed Time Series
Title
Heavy-Tailed Time Series
Statement of responsibility
by Rafal Kulik, Philippe Soulier
Creator
Contributor
Author
Subject
Language
eng
Summary
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.--
Member of
Assigning source
Provided by publisher
http://library.link/vocab/creatorName
Kulik, Rafal
Image bit depth
0
Literary form
non fiction
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorName
Soulier, Philippe
Series statement
  • Springer Series in Operations Research and Financial Engineering,
  • Springer eBooks.
http://library.link/vocab/subjectName
  • Probabilities
  • Statistics
  • Applied mathematics
  • Engineering mathematics
Label
Heavy-Tailed Time Series, by Rafal Kulik, Philippe Soulier, (electronic resource)
Link
https://eui.idm.oclc.org/login?url=https://doi.org/10.1007/978-1-0716-0737-4
Instantiates
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
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.
Control code
978-1-0716-0737-4
Dimensions
unknown
Edition
1st ed. 2020.
Extent
1 online resource (XIX, 681 pages)
File format
multiple file formats
Form of item
  • online
  • electronic
Isbn
9781071607374
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other physical details
7 illustrations, 5 illustrations in color.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
(OCoLC)1164491680
Label
Heavy-Tailed Time Series, by Rafal Kulik, Philippe Soulier, (electronic resource)
Link
https://eui.idm.oclc.org/login?url=https://doi.org/10.1007/978-1-0716-0737-4
Publication
Antecedent source
mixed
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
not applicable
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
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.
Control code
978-1-0716-0737-4
Dimensions
unknown
Edition
1st ed. 2020.
Extent
1 online resource (XIX, 681 pages)
File format
multiple file formats
Form of item
  • online
  • electronic
Isbn
9781071607374
Level of compression
uncompressed
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other physical details
7 illustrations, 5 illustrations in color.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
System control number
(OCoLC)1164491680

Library Locations

    • Badia FiesolanaBorrow it
      Via dei Roccettini 9, San Domenico di Fiesole, 50014, IT
      43.803074 11.283055
Processing Feedback ...