Paul Doukhan

Gabriel Lang

Jrme Dedecker

José Rafael León R.

Sana Louhichi

José Rafael Leon

Clémentine Prieur

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

Donatas Surgailis

Gilles Teyssière

This account of recent works on weakly dependent, long memory and multifractal processes introduces new dependence measures for studying complex stochastic systems and includes other topics such as the dependence structure of max-stable processes.

Dependence in Probability and Statistics

Gabriel Lang

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