| Dependence in Probability and Statistics Contributor(s): Doukhan, Paul (Editor), Lang, Gabriel (Editor), Surgailis, Donatas (Editor) |
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ISBN: 364214103X ISBN-13: 9783642141034 Publisher: Springer OUR PRICE: $52.24 Product Type: Paperback - Other Formats Published: August 2010 |
| Additional Information |
| BISAC Categories: - Mathematics | Probability & Statistics - General - Mathematics | Counting & Numeration - Computers | Mathematical & Statistical Software |
| Dewey: 519 |
| Series: Lecture Notes in Statistics |
| Physical Information: 0.48" H x 6.14" W x 9.21" (0.72 lbs) 205 pages |
| Descriptions, Reviews, Etc. |
| Publisher Description: 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, Horv th 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. |