ENGLISH

Dependence in probability and statistics

By Paul Doukhan , Gabriel Lang , Lajos Horváth , István Berkes , Johannes Schauer (auth.) , Donatas Surgailis , Gilles Teyssière (eds.)

Book information

Publisher
Springer-Verlag Berlin Heidelberg
Year
2010
ISBN
364214103X, 9783642141034
DOI
10.1007/978-3-642-14104-1
Open Library ID
OL25202202M
Language
english
Format
PDF
Filesize
2 MB (1620963 bytes)
Series
Lecture Notes in Statistics 200
Edition
1
Pages
205\224
Library
Kolxo3
Time added
2011-07-22 07:35:22
Statistics and Computing/Statistics Programs; Stat

Description

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.

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