Dedecker / Doukhan / Lang Weak Dependence: With Examples and Applications
2007
ISBN: 978-0-387-69952-3
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark
E-Book, Englisch, Band 190, 322 Seiten, eBook
Reihe: Lecture Notes in Statistics
ISBN: 978-0-387-69952-3
Verlag: Springer US
Format: PDF
Kopierschutz: 1 - PDF Watermark
This book develops Doukhan/Louhichi's 1999 idea to measure asymptotic independence of a random process. The authors, who helped develop this theory, propose examples of models fitting such conditions: stable Markov chains, dynamical systems or more complicated models, nonlinear, non-Markovian, and heteroskedastic models with infinite memory. Applications are still needed to develop a method of analysis for nonlinear times series, and this book provides a strong basis for additional studies.
Zielgruppe
Professional/practitioner
Autoren/Hrsg.
Weitere Infos & Material
Weak dependence.- Models.- Tools for non causal cases.- Tools for causal cases.- Applications of strong laws of large numbers.- Central Limit theorem.- Donsker Principles.- Law of the iterated logarithm (LIL).- The Empirical process.- Functional estimation.- Spectral estimation.- Econometric applications and resampling.
