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Titlebook: Breakthroughs in Statistics; Samuel Kotz,Norman L. Johnson Book 1997 Springer Science+Business Media New York 1997 algorithms.boundary ele

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发表于 2025-3-23 12:30:44 | 显示全部楼层
Book 1997so available: Breakthroughs in Statistics Volume I: Foundations and Basic Theory Samuel Kotz and Norman L. Johnson, Editors 1993. 631 pp. Softcover. ISBN 0-387-94037-5 Breakthroughs in Statistics Volume II: Methodology and Distribution Samuel Kotz and Norman L. Johnson, Editors 1993. 600 pp. Softcover. ISBN 0-387-94039-1
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Pauline Alderson,Martin Rowlandealistic and solvable. It was also the case the Bayesian modeling did not find general acceptance unless it could be shown that such models had desirable frequentist properties. Thus, when viewed in this context, this contribution by Lindley and Smith (hereafter LS) must surely qualify for the accolade, “breakthrough.”
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Pauline Alderson,Martin Rowland and Green (1993); Besag et al. (1995)]. His first major paper, however, laid out the foundations for statistical inference in lattice systems, and so provided the background for much later work, both his own and that of many others.
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, Levit (1974) On the Optimality of Some Statistical Estimates,singly long to realize that the idea of asymptotic efficiency as originally conceived was too naive. The reason for this is, perhaps, that the admirable intuition of the early statisticians was not kept in control by the requirement of mathematical rigor.
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, Rousseeuw (1984) Least Median of Squares Regression,ated a finite-sample version of the breakdown value, in line with Hodges’s (1967) study in the univariate framework. Heuristically, the . is the largest percentage of ill-fitting data that a method can cope with. For a formal definition, see equation (2.1) of the reprinted Rousseeuw (1984).
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0172-7397 ct - All articles that are included have initiated fundamentThis is author-approved bcc: This is the third volume of a collection of seminal papers in the statistical sciences written during the past 110 years. These papers have each had an outstanding influence on the development of statistical the
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Automotive Pollution Control Technologiessive for applications in statistics, occurred when Geman and Geman (1984) wrestled the seminal idea of Metropolis et al. from its statistical mechanics surroundings, modified it, and applied it to Bayesian modeling and the computation of posterior distributions in otherwise intractable situations.
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