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Springer Series in Operations Research and Financial Engineering

Univariate Stable Distributions

Models for Heavy Tailed Data

Authors: Nolan, John P.

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  • Introduces the theory, numerical algorithms, and statistical methods associated with stable distributions with an accessible, non-technical approach
  • Highlights the many practical applications of stables distributions, including in finance, statistics, engineering, physics, and more
  • Presents a number of helpful exercises, as well as links to free software to apply the models in practice
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書籍の購入

イーブック ¥3,774
¥7,435 (listprice)
価格の適用国: Japan (日本円価格は個人のお客様のみ有効) (小計)
有効期限: June 30, 2021
  • ISBN 978-3-030-52915-4
  • ウォーターマーク付、 DRMフリー
  • ファイル形式: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
ハードカバー ¥4,718
¥9,294 (listprice)
価格の適用国: Japan (日本円価格は個人のお客様のみ有効) (小計)
有効期限: June 30, 2021
  • ISBN 978-3-030-52914-7
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
この教本について

This textbook highlights the many practical uses of stable distributions, exploring the theory, numerical algorithms, and statistical methods used to work with stable laws. Because of the author’s accessible and comprehensive approach, readers will be able to understand and use these methods. Both mathematicians and non-mathematicians will find this a valuable resource for more accurately modelling and predicting large values in a number of real-world scenarios.
Beginning with an introductory chapter that explains key ideas about stable laws, readers will be prepared for the more advanced topics that appear later. The following chapters present the theory of stable distributions, a wide range of applications, and statistical methods, with the final chapters focusing on regression, signal processing, and related distributions. Each chapter ends with a number of carefully chosen exercises. Links to free software are included as well, where readers can put these methods into practice.
Univariate Stable Distributions is ideal for advanced undergraduate or graduate students in mathematics, as well as many other fields, such as statistics, economics, engineering, physics, and more. It will also appeal to researchers in probability theory who seek an authoritative reference on stable distributions.

著者について

​John Nolan received his PhD from the University of Virginia, and has taught at the University of Zambia, Kenyon College, and American University. He also worked in a software firm, developing systems for intensive care units. His main research interests are in models for heavy tailed data and extremes.

レビュー

“This book is an excellent reference for researchers and practitioners looking to make use of both the rich theory and applicability offered by stable distributions. The text is clear and accessible throughout, including all the necessary mathematical and statistical details to make it both a thorough and practical work on univariate modelling using stable distributions.” (Fraser Daly, zbMATH 1455.62003, 2021)


Table of contents (7 chapters)

Table of contents (7 chapters)

書籍の購入

イーブック ¥3,774
¥7,435 (listprice)
価格の適用国: Japan (日本円価格は個人のお客様のみ有効) (小計)
有効期限: June 30, 2021
  • ISBN 978-3-030-52915-4
  • ウォーターマーク付、 DRMフリー
  • ファイル形式: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
ハードカバー ¥4,718
¥9,294 (listprice)
価格の適用国: Japan (日本円価格は個人のお客様のみ有効) (小計)
有効期限: June 30, 2021
  • ISBN 978-3-030-52914-7
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
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書誌情報

Bibliographic Information
Book Title
Univariate Stable Distributions
Book Subtitle
Models for Heavy Tailed Data
Authors
Series Title
Springer Series in Operations Research and Financial Engineering
Copyright
2020
Publisher
Springer International Publishing
Copyright Holder
The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG
イーブック ISBN
978-3-030-52915-4
DOI
10.1007/978-3-030-52915-4
ハードカバー ISBN
978-3-030-52914-7
Series ISSN
1431-8598
Edition Number
1
Number of Pages
XV, 333
Number of Illustrations
83 b/w illustrations, 21 illustrations in colour
Topics