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Titlebook: Case Studies in Bayesian Statistics; Constantine Gatsonis,James S. Hodges,Nozer D. Sing Conference proceedings 1993 Springer-Verlag New Yo

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書目名稱Case Studies in Bayesian Statistics
編輯Constantine Gatsonis,James S. Hodges,Nozer D. Sing
視頻videohttp://file.papertrans.cn/223/222242/222242.mp4
叢書名稱Lecture Notes in Statistics
圖書封面Titlebook: Case Studies in Bayesian Statistics;  Constantine Gatsonis,James S. Hodges,Nozer D. Sing Conference proceedings 1993 Springer-Verlag New Yo
描述The past few years have witnessed dramatic advances in computational methods for Bayesian inference. As a result, Bayesian approaches to solving a wide variety of problems in data analysis and decision-making have become feasible, and there is currently a growth spurt in the application of Bayesian methods. The purpose of this volume is to present several detailed examples of applications of Bayesian thinking, with an emphasis on the scientific or technological context of the problem being solved. The papers collected here were presented and discussed at a Workshop held at Carnegie-Mellon University, September 29 through October 1, 1991. There are five ma- jor articles, each with two discussion pieces and a reply. These articles were invited by us following a public solicitation of abstracts. The problems they address are diverse, but all bear on policy decision-making. Though not part of our original design for the Workshop, that commonality of theme does emphasize the usefulness of Bayesian meth- ods in this arena. Along with the invited papers were several additional commentaries of a general nature; the first comment was invited and the remainder grew out of the discussion at t
出版日期Conference proceedings 1993
關(guān)鍵詞bayesian statistics; data analysis; statistics
版次1
doihttps://doi.org/10.1007/978-1-4612-2714-4
isbn_softcover978-0-387-94043-4
isbn_ebook978-1-4612-2714-4Series ISSN 0930-0325 Series E-ISSN 2197-7186
issn_series 0930-0325
copyrightSpringer-Verlag New York, Inc. 1993
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978-0-387-94043-4Springer-Verlag New York, Inc. 1993
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Toxicity and Carcinogenicity of Metals, much of an increase in fuel economy is possible through implementation of existing technology?.This question is studied using an EPA data base of over 3000 vehicles. The data analysis was done using a hierarchical Bayesian (random effects) model, with computations being performed via Gibbs sampling
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SEaTH – A New Tool for Feature Analysis drug treatment. In order to limit the subjects exposed to extreme toxicity, the dose levels used in the experiment are chosen to minimize the predicted posterior variance of the target dose. To further limit toxicity, the experiment was conducted by sequentially allocating treatments to groups usin
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eCognition Image Analysis Softwarein electronic and physical characteristics, and are thus considered to be different products. The automatic sorting of these wafers, called ‘bin splitting’, leads to variable joint output in the different product categories. Prediction of future coproduct output is of obvious importance in productio
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Rationality of Legal Reasoning,sian predictive inference to provide point estimates and measures of variability for the desired finite population quantities. Our investigation concerns binary random variables such as the occurrence of at least one doctor visit within the past twelve months..Our specification, similar to that of W
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