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Titlebook: Empirical Bayes and Likelihood Inference; S. E. Ahmed,N. Reid Book 2001 Springer Science+Business Media New York 2001 Estimator.Likelihood

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书目名称Empirical Bayes and Likelihood Inference
编辑S. E. Ahmed,N. Reid
视频video
丛书名称Lecture Notes in Statistics
图书封面Titlebook: Empirical Bayes and Likelihood Inference;  S. E. Ahmed,N. Reid Book 2001 Springer Science+Business Media New York 2001 Estimator.Likelihood
描述Bayesian and likelihood approaches to inference have a number of points of close contact, especially from an asymptotic point of view. Both approaches emphasize the construction of interval estimates of unknown parameters. Empirical Bayes methods have historically emphasized instead the construction of point estimates. In this volume researchers present recent work on several aspects of Bayesian, likelihood and empirical Bayes methods, presented at a workshop held in Montreal, Canada. The goal of the workshop was to explore the linkages among the methods, and to suggest new directions for research in the theory of inference.
出版日期Book 2001
关键词Estimator; Likelihood; Variance; algorithms; analysis of variance; expectation–maximization algorithm
版次1
doihttps://doi.org/10.1007/978-1-4613-0141-7
isbn_softcover978-0-387-95018-1
isbn_ebook978-1-4613-0141-7Series ISSN 0930-0325 Series E-ISSN 2197-7186
issn_series 0930-0325
copyrightSpringer Science+Business Media New York 2001
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https://doi.org/10.1007/978-3-658-35687-3y . = (.. ... ..) of . linearly independent vectors tangent to the ancillary surface at the observed data. For the two types of ancillarity simple expressions for the array . are given; these are obtained from a full dimensional pivotal quantity. A brief summary describes the use of . to obtain seco
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Bayes/EB Ranking, Histogram and Parameter Estimation: Issues and Research Agenda, requirement leads to development of “triple-goal” estimates: those producing a histogram that is a good estimate of the parameter histogram, with induced ranks that are good estimates of the parameter ranks and with good performance in estimating unit-specific parameters. Using mathematical and sim
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Ancillary Information for Statistical Inference,y . = (.. ... ..) of . linearly independent vectors tangent to the ancillary surface at the observed data. For the two types of ancillarity simple expressions for the array . are given; these are obtained from a full dimensional pivotal quantity. A brief summary describes the use of . to obtain seco
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Cordula Grunow-Erdmann,Karl-Heinz ErdmannBayes and empirical Bayes estimates of the survival and hazard functions of a class of distributions are obtained. These estimates are compared with the corresponding maximum likelihood estimates. A Monte Carlo study is designed to perform this comparison, due to intractability of the estimators distributions from an analytical point of view.
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