Dependence in Probability and Statistics (Lecture Notes in Statistics, 200) - Softcover

Softcover

ISBN 10: 364214103X ISBN 13: 9783642141034

Publisher: Springer, 2010

Synopsis

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.

About this title

From the Back Cover

This volume collects recent works on weakly dependent, long-memory and multifractal processes and introduces new dependence measures for studying complex stochastic systems. Other topics include the statistical theory for bootstrap and permutation statistics for infinite variance processes, the dependence structure of max-stable processes, and the statistical properties of spectral estimators of the long memory parameter. The asymptotic behavior of Fejér graph integrals and their use for proving central limit theorems for tapered estimators are investigated. New multifractal processes are introduced and their multifractal properties analyzed. Wavelet-based methods are used to study multifractal processes with different multiresolution quantities, and to detect changes in the variance of random processes. Linear regression models with long-range dependent errors are studied, as is the issue of detecting changes in their parameters.

Edition details

• Publisher: Springer
• Publication date: 2010
• Language: English
• ISBN 10: 364214103X
• ISBN 13: 9783642141034
• Binding: Paperback
• Number of pages: 220
• Editor: Doukhan Paul, Lang Gabriel, Surgailis Donatas, Teyssière Gilles