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Titlebook: Advances in the Statistical Sciences: Foundations of Statistical Inference; Volume II of the Fes Ian B. MacNeill,Gary J. Umphrey,Serge B. P

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51#
發(fā)表于 2025-3-30 09:50:28 | 只看該作者
52#
發(fā)表于 2025-3-30 15:48:38 | 只看該作者
53#
發(fā)表于 2025-3-30 17:24:19 | 只看該作者
Contemporary Issues in Accountings meant for prospective assessment of uncertainty. Widespread opportunities exist for developing statistics along these lines, through practical attempts to bridge the gap from evidence to probability representations in appropriately selected domains of science. Illustrations are drawn from policy-r
54#
發(fā)表于 2025-3-30 22:22:00 | 只看該作者
55#
發(fā)表于 2025-3-31 02:10:20 | 只看該作者
Contemporary Issues in Accounting Regulationof sufficiency and conditionality is an underlying intention of separating . from .. This manifests itself in the ordinary analysis of variance and also for the generalizations of that analysis for the transformation models and for the exponential models. This paper gives preliminary introduction to
56#
發(fā)表于 2025-3-31 08:55:39 | 只看該作者
Mawuadem Koku Amedeker,Thomas Tachie Younginterest. The likelihood factorizes and the partial likelihood depends on. alone. This paper examines the problem of making inferences about. in detail and concludes that although the partial likelihood method is asymptotically sound the approach to the limit is slow, so that the method can lose a l
57#
發(fā)表于 2025-3-31 12:35:06 | 只看該作者
Language Proficiency and Science Learning,s. The resulting best binary decision criterion is everywhere randomized, the probability of choosing. = 1 as opposed to. = 0, being given by.where.. is the loss due to the wrong decision when θ is the state of Nature, where f. is a density, and where . is the outcome.
58#
發(fā)表于 2025-3-31 15:42:48 | 只看該作者
59#
發(fā)表于 2025-3-31 19:37:45 | 只看該作者
60#
發(fā)表于 2025-3-31 22:31:44 | 只看該作者
Moriki Hosoe,Tadahisa Ohno,Akio Kawasakimputation of the maximum likelihood (normality) or least squares fit is available for the isotonic case in a bounded number of steps. For the concave case most of the algorithms have been difficult to implement or had no assured convergence; Dykstra (1983) gave an algorithm easy to implement and con
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