Shortcuts
Top of page (Alt+0)
Page content (Alt+9)
Page menu (Alt+8)
Your browser does not support javascript, some WebOpac functionallity will not be available.
.
Default
.
PageMenu
-
Main Menu
-
Simple Search
.
Advanced Search
.
Journal Search
.
Refine Search Results
.
Preferences
.
Search Menu
Simple Search
.
Advanced Search
.
New Items Search
.
Journal Search
.
Refine Search Results
.
Bottom Menu
Help
Italian
.
English
.
German
.
New Item Menu
New Items Search
.
New Items List
.
Links
SISSA Library
.
ICTP library
.
Italian National web catalog (SBN)
.
Trieste University web catalog
.
Udine University web catalog
.
© LIBERO v6.4.1sp220816
Page content
You are here
:
Catalogue Display
Catalogue Display
Stochastic Models for Time Series
.
Bookmark this Record
Catalogue Record 37797
.
.
Author info on Wikipedia
.
.
LibraryThing
.
.
Google Books
.
.
Amazon Books
.
Catalogue Information
Catalogue Record 37797
.
Reviews
Catalogue Record 37797
.
British Library
Resolver for RSN-37797
Google Scholar
Resolver for RSN-37797
WorldCat
Resolver for RSN-37797
Catalogo Nazionale SBN
Resolver for RSN-37797
GoogleBooks
Resolver for RSN-37797
ICTP Library
Resolver for RSN-37797
.
Share Link
Jump to link
Catalogue Information
Field name
Details
Dewey Class
519.5
Title
Stochastic Models for Time Series ([EBook]) / by Paul Doukhan.
Author
Doukhan, Paul
Other name(s)
SpringerLink (Online service)
Publication
Cham : : Springer International Publishing : : Imprint: Springer, , 2018.
Physical Details
XX, 308 p. 29 illus., 10 illus. in color. : online resource.
Series
Mathématiques et Applications
1154-483X ; ; 80
ISBN
9783319769387
Summary Note
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 a tour of linear time series models. It goes on to address nonlinearity from polynomial or chaotic models for which explicit expansions are available, then turns to Markov and non-Markov linear models and discusses Bernoulli shifts time series models. Finally, the volume focuses on the limit theory, starting with the ergodic theorem, which is seen as the first step for statistics of time series. It defines the distributional range to obtain generic tools for limit theory under long or short-range dependences (LRD/SRD) and explains examples of LRD behaviours. More general techniques (central limit theorems) are described under SRD; mixing and weak dependence are also reviewed. In closing, it describes moment techniques together with their relations to cumulant sums as well as an application to kernel type estimation.The appendix reviews basic probability theory facts and discusses useful laws stemming from the Gaussian laws as well as the basic principles of probability, and is completed by R-scripts used for the figures. Richly illustrated with examples and simulations, the book is recommended for advanced master courses for mathematicians just entering the field of time series, and statisticians who want more mathematical insights into the background of non-linear time series. .:
Contents note
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.
System details note
Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users)
Internet Site
http://dx.doi.org/10.1007/978-3-319-76938-7
Links to Related Works
Subject References:
Dynamical systems and ergodic theory
.
Dynamics
.
Econometrics
.
Ergodic theory
.
Probabilities
.
Probability theory and stochastic processes
.
Statistical Theory and Methods
.
Statistics
.
Authors:
Doukhan, Paul
.
Corporate Authors:
SpringerLink (Online service)
.
Series:
Mathématiques et Applications
.
Classification:
519.5
.
.
ISBD Display
Catalogue Record 37797
.
Tag Display
Catalogue Record 37797
.
Related Works
Catalogue Record 37797
.
Marc XML
Catalogue Record 37797
.
Add Title to Basket
Catalogue Record 37797
.
Catalogue Information 37797
Beginning of record
.
Catalogue Information 37797
Top of page
.
Download Title
Catalogue Record 37797
Export
This Record
As
Labelled Format
Bibliographic Format
ISBD Format
MARC Format
MARC Binary Format
MARCXML Format
User-Defined Format:
Title
Author
Series
Publication Details
Subject
To
File
Email
Reviews
This item has not been rated.
Add a Review and/or Rating
37797
1
37797
-
2
37797
-
3
37797
-
4
37797
-
5
37797
-
Quick Search
Search for