000 03410nam a22004815i 4500
001 978-3-642-14104-1
003 DE-He213
005 20140220084541.0
007 cr nn 008mamaa
008 100726s2010 gw | s |||| 0|eng d
020 _a9783642141041
_9978-3-642-14104-1
024 7 _a10.1007/978-3-642-14104-1
_2doi
050 4 _aQA276-280
072 7 _aUFM
_2bicssc
072 7 _aCOM077000
_2bisacsh
082 0 4 _a519.5
_223
100 1 _aDoukhan, Paul.
_eeditor.
245 1 0 _aDependence in Probability and Statistics
_h[electronic resource] /
_cedited by Paul Doukhan, Gabriel Lang, Donatas Surgailis, Gilles Teyssière.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2010.
300 _aXV, 205p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Statistics,
_x0930-0325 ;
_v200
505 0 _aPermutation and bootstrap statistics under infinite variance -- Max–Stable Processes: Representations, Ergodic Properties and Statistical Applications -- Best attainable rates of convergence for the estimation of the memory parameter -- Harmonic analysis tools for statistical inference in the spectral domain -- On the impact of the number of vanishing moments on the dependence structures of compound Poisson motion and fractional Brownian motion in multifractal time -- Multifractal scenarios for products of geometric Ornstein-Uhlenbeck type processes -- A new look at measuring dependence -- Robust regression with infinite moving average errors -- A note on the monitoring of changes in linear models with dependent errors -- Testing for homogeneity of variance in the wavelet domain.
520 _aThis 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.
650 0 _aStatistics.
650 0 _aMathematical statistics.
650 1 4 _aStatistics.
650 2 4 _aStatistics and Computing/Statistics Programs.
650 2 4 _aStatistical Theory and Methods.
700 1 _aLang, Gabriel.
_eeditor.
700 1 _aSurgailis, Donatas.
_eeditor.
700 1 _aTeyssière, Gilles.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642141034
830 0 _aLecture Notes in Statistics,
_x0930-0325 ;
_v200
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-14104-1
912 _aZDB-2-SMA
999 _c112411
_d112411