Dependence in Probability and Statistics (Paperback, Edition.)

This volume contains several contributions on the general theme of dependence for several classes of stochastic processes, andits implicationson asymptoticproperties of various statistics and on statistical inference issues in statistics and econometrics. The chapter by Berkes, Horvath and Schauer is a survey on their recent results on bootstrap and permutation statistics when the negligibility condition of classical central limit theory is not satis ed. These results are of interest for describing the asymptotic properties of bootstrap and permutation statistics in case of in nite va- ances, and for applications to statistical inference, e.g., the change-point problem. The paper by Stoev reviews some recent results by the author on ergodicity of max-stable processes. Max-stable processes play a central role in the modeling of extreme value phenomena and appear as limits of component-wise maxima. At the presenttime, arathercompleteandinterestingpictureofthedependencestructureof max-stable processes has emerged, involvingspectral functions, extremalstochastic integrals, mixed moving maxima, and other analytic and probabilistic tools. For statistical applications, the problem of ergodicity or non-ergodicity is of primary importance.

General

Imprint:	Springer-Verlag
Country of origin:	Germany
Series:	Lecture Notes in Statistics, 200
Release date:	August 2010
First published:	August 2010
Editors:	Paul Doukhan • Gabriel Lang • Donatas Surgailis • Gilles Teyssiere
Dimensions:	235 x 155 x 12mm (L x W x T)
Format:	Paperback
Pages:	205
Edition:	Edition.
ISBN-13:	978-3-642-14103-4
Categories:	Books > Science & Mathematics > Mathematics > Numerical analysis Books > Science & Mathematics > Mathematics > Probability & statistics Books > Computing & IT > Computer software packages > Other software packages > Mathematical & statistical software
LSN:	3-642-14103-X
Barcode:	9783642141034

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