Weak Dependence: With Examples and Applications

This monograph is aimed at developing Doukhan/Louhichi's (1999) idea to measure asymptotic independence of a random process. The authors propose various examples of models fitting such conditions such as stable Markov chains, dynamical systems or more complicated models, nonlinear, non-Markovia...

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Detalles Bibliográficos
Autores principales: Dedecker, Jérôme, Doukhan, Paul, Lang, Gabriel
Lenguaje:eng
Publicado: Springer 2007
Materias:
Mathematical Physics and Mathematics
Acceso en línea:https://dx.doi.org/10.1007/978-0-387-69952-3
http://cds.cern.ch/record/1338284
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author Dedecker, Jérôme
Doukhan, Paul
Lang, Gabriel
author_facet Dedecker, Jérôme
Doukhan, Paul
Lang, Gabriel
author_sort Dedecker, Jérôme
collection CERN
description This monograph is aimed at developing Doukhan/Louhichi's (1999) idea to measure asymptotic independence of a random process. The authors propose various examples of models fitting such conditions such as stable Markov chains, dynamical systems or more complicated models, nonlinear, non-Markovian, and heteroskedastic models with infinite memory. Most of the commonly used stationary models fit their conditions. The simplicity of the conditions is also their strength. The main existing tools for an asymptotic theory are developed under weak dependence. They apply the theory to nonparametric stati
id cern-1338284
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2007
publisher Springer
record_format invenio
spelling cern-13382842021-04-22T01:06:54Zdoi:10.1007/978-0-387-69952-3http://cds.cern.ch/record/1338284engDedecker, JérômeDoukhan, PaulLang, GabrielWeak Dependence: With Examples and ApplicationsMathematical Physics and MathematicsThis monograph is aimed at developing Doukhan/Louhichi's (1999) idea to measure asymptotic independence of a random process. The authors propose various examples of models fitting such conditions such as stable Markov chains, dynamical systems or more complicated models, nonlinear, non-Markovian, and heteroskedastic models with infinite memory. Most of the commonly used stationary models fit their conditions. The simplicity of the conditions is also their strength. The main existing tools for an asymptotic theory are developed under weak dependence. They apply the theory to nonparametric statiSpringeroai:cds.cern.ch:13382842007
spellingShingle Mathematical Physics and Mathematics
Dedecker, Jérôme
Doukhan, Paul
Lang, Gabriel
Weak Dependence: With Examples and Applications
title Weak Dependence: With Examples and Applications
title_full Weak Dependence: With Examples and Applications
title_fullStr Weak Dependence: With Examples and Applications
title_full_unstemmed Weak Dependence: With Examples and Applications
title_short Weak Dependence: With Examples and Applications
title_sort weak dependence: with examples and applications
topic Mathematical Physics and Mathematics
url https://dx.doi.org/10.1007/978-0-387-69952-3
http://cds.cern.ch/record/1338284
work_keys_str_mv AT dedeckerjerome weakdependencewithexamplesandapplications
AT doukhanpaul weakdependencewithexamplesandapplications
AT langgabriel weakdependencewithexamplesandapplications

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