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Stochastic models for time series

Author: Paul Doukhan
Publisher: Cham : Springer, 2018.
Series: Mathématiques & applications, 80.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
This book presents essential tools for modelling non-linear time series. The first part of the book describes the main standard tools of probability and statistics that directly apply to the time series context to obtain a wide range of modelling possibilities. Functional estimation and bootstrap are discussed, and stationarity is reviewed. The second part describes a number of tools from Gaussian chaos and proposes  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Printed edition:
(OCoLC)1022079439
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Paul Doukhan
ISBN: 9783319769387 3319769383
OCLC Number: 1034550830
Description: 1 online resource (xx, 308 pages) : illustrations
Contents: Part I Independence and Stationarity --
1 Probability and Independence --
2 Gaussian convergence and inequalities --
3 Estimation concepts --
4 Stationarity --
Part II Models of time series --
5 Gaussian chaos --
6 Linear processes --
7 Non-linear processes --
8 Associated processes --
Part III Dependence --
9 Dependence --
10 Long-range dependence --
11 Short-range dependence --
12 Moments and cumulants --
Appendices --
A Probability and distributions --
B Convergence and processes --
C R scripts used for the gures --
Index- List of figures.
Series Title: Mathématiques & applications, 80.
Responsibility: Paul Doukhan.

Abstract:

This book presents essential tools for modelling non-linear time series.  Read more...

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"We are dealing with a monograph that compiles a broad set of fundamental results on the probabilistic and statistical analysis of time series, and is mathematically rigorous and effectively suitable Read more...

 
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