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SpringerBriefs in Computer Science
cover

Asymptotic Nonparametric Statistical Analysis of Stationary Time Series

Authors: Ryabko, Daniil

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eBook 41,64 €
price for Spain (gross)
  • The eBook version of this title will be available soon
  • Due: April 19, 2019
  • ISBN 978-3-030-12564-6
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Softcover 51,99 €
price for Spain (gross)
  • Due: April 19, 2019
  • ISBN 978-3-030-12563-9
  • Free shipping for individuals worldwide
  • The final prices may differ from the prices shown due to specifics of VAT rules
About this book

Stationarity is a very general, qualitative assumption, that can be assessed on the basis of application specifics. It is thus  a rather attractive assumption to base statistical analysis on, especially for problems for which less general qualitative assumptions, such as independence or finite memory, clearly fail. However, it has long been considered too general to be able to make statistical inference. One of the reasons for this is that rates of convergence, even of frequencies to the mean, are not available under this assumption alone.  Recently, it has been shown that, while some natural and simple problems, such as homogeneity, are indeed provably impossible to solve if one only assumes that the data is stationary (or stationary ergodic), many others can be solved with rather simple and intuitive algorithms. The latter include clustering and change point estimation among others. In this volume I summarize these  results.  The emphasis is on asymptotic consistency, since this the strongest property one can obtain assuming stationarity alone. While for most of the problem for which  a solution is found this solution is algorithmically realizable, the main objective in this area of research, the objective which is only partially attained, is to understand what is possible and what is not possible to do for stationary time series. The considered problems include homogeneity testing (the so-called two sample problem), clustering with respect to distribution, clustering with respect to independence, change point estimation, identity testing, and the general problem of composite hypotheses testing. For the latter problem, a topological criterion for the existence of a consistent test is presented.  In addition, a number of open problems is presented.

Buy this book

eBook 41,64 €
price for Spain (gross)
  • The eBook version of this title will be available soon
  • Due: April 19, 2019
  • ISBN 978-3-030-12564-6
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Softcover 51,99 €
price for Spain (gross)
  • Due: April 19, 2019
  • ISBN 978-3-030-12563-9
  • Free shipping for individuals worldwide
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
Asymptotic Nonparametric Statistical Analysis of Stationary Time Series
Authors
Series Title
SpringerBriefs in Computer Science
Copyright
2019
Publisher
Springer International Publishing
Copyright Holder
The Author(s), under exclusive license to Springer Nature Switzerland AG
eBook ISBN
978-3-030-12564-6
DOI
10.1007/978-3-030-12564-6
Softcover ISBN
978-3-030-12563-9
Series ISSN
2191-5768
Edition Number
1
Number of Pages
VIII, 92
Number of Illustrations
4 b/w illustrations
Topics