Weak Dependence With Examples and Applications, Paperback by Dedecker, Jerome...

$ 84.56

Format: Perfect Publication Name: Weak Dependence : with Examples and Applications Number of Pages: Xiv, 322 Pages Author: Sana Louhichi, Paul Doukhan, José Rafael León, Jérôme Dedecker, Gabriel Lang Item Height: 0.2 in Item Weight: 18.2 Oz Publisher: Springer New York Item Width: 6.1 in Publication Year: 2007 Language: English Subject: Probability & Statistics / Stochastic Processes, Probability & Statistics / General, Algebra / General Type: Textbook Book Title: Weak Dependence With Examples and Applications Series: Lecture Notes in Statistics Ser. Subject Area: Mathematics width: 6.1 in ISBN: 9780387699516 height: 0.2 in Item Length: 9.3 in

Description

Weak Dependence With Examples and Applications, Paperback by Dedecker, Jerome.... Weak Dependence With Examples and Applications, Paperback by Dedecker, Jerome; Doukhan, Paul; Lang, Gabriel; Leon, Jose Rafael; Louhichi, Sana, ISBN 0387699511, ISBN-13 9780387699516, Brand New, Free shipping in the US 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. Weak Dependence With Examples and Applications, Paperback by Dedecker, Jerome; Doukhan, Paul; Lang, Gabriel; Leon, Jose Rafael; Louhichi, Sana, ISBN 0387699511, ISBN-13 9780387699516, Brand New, Free shipping in the US 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.