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viii, 492p., stiff library boards, ex libris (Lecture notes in statistics, 187).
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Paperback. Condition: new. Paperback. 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Published by Chapman and Hall/CRC, 2023
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Published by Chapman and Hall/CRC, 1997
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Paperback or Softback. Condition: New. Dependence in Probability and Statistics. Book.
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Published by Chapman and Hall/CRC, 1997
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Hardcover. Condition: Good. Hardcover. No dust jacket. Good binding and cover. Scattered marks/highlighting. xviii, 399 pages : illustrations ; 22 cm. This book on multivariate models, statistical inference, and data analysis contains deep coverage of multivariate non-normal distributions for modeling of binary, count, ordinal, and extreme value response data.
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