{"title":"Mathematics","description":"","products":[{"product_id":"bayesian-methods-for-finite-population-sampling-79-chapman-hall-crc-monographs-on-statistics-and-applied-probability","title":"Bayesian Methods for Finite Population Sampling: 79 (Chapman \u0026 Hall\/CRC Monographs on Statistics and Applied Probability)","description":"\u003cp\u003e\u003cb\u003eAuthor:\u003c\/b\u003e Ghosh, Malay\u003c\/p\u003e\u003cp\u003e\u003cb\u003eBrand:\u003c\/b\u003e Routledge\u003c\/p\u003e\u003cp\u003e\u003cb\u003eEdition:\u003c\/b\u003e 1\u003c\/p\u003e\u003cp\u003e\u003cb\u003eBinding:\u003c\/b\u003e hardcover\u003c\/p\u003e\u003cp\u003e\u003cb\u003eFormat:\u003c\/b\u003e Import\u003c\/p\u003e\u003cp\u003e\u003cb\u003eNumber Of Pages:\u003c\/b\u003e 300\u003c\/p\u003e\u003cp\u003e\u003cb\u003eRelease Date:\u003c\/b\u003e 01-01-1997\u003c\/p\u003e\u003cp\u003e\u003cb\u003eDetails:\u003c\/b\u003e Product Description\u003cbr\u003e\n\u003cbr\u003e\n\u003cbr\u003e\nThe present monograph is primarily an outgrowth of our own re­ search on certain aspects of Bayesian inference in finite population sampling. Finite population sampling has been an integral part of statistics since its beginning. The topic continues its impact in the theory and practice of statistics, especially for researchers in survey sampling. Inference for finite population sampling utilizes prior information either explicitly or implicitly. Bayesian inference makes explicit use of this information as part of the model. This is in striking con­ trast to design- based inference in survey sampling where prior knowledge is incorporated only as auxiliary information. On the other hand there is a elose relationship between the Bayesian ap­ proach and the superpopulation approach, although they differ in their foundational interpretations. Operationally, however, the dif­ ference is much less pronounced as many estimators obtained via superpopulation models are also obtainable as Bayes estimators, and vice versa. This monograph, does not aim to provide a complete up-to-date account of the Bayesian literature in finite population sampling. Rather, it treats the topics reflecting the authors' personal inter­ ests. Its main aim is to demonstrate that a variety of levels of prior information can be used in survey sampling in a Bayesian man­ ner. 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Barrow is Professor of Mathematical Sciences and Director of the Millennium Mathematics Project at Cambridge University, Fellow of Clare Hall, Cambridge, a Fellow of the Royal Society, and formerly Professor of both Geometry and Astronomy at Gresham College, London. His previous books include\u003cbr\u003e\nThe Book of Nothing,\u003cbr\u003e\n The Constants of Nature,\u003cbr\u003e\nThe Infinite Book,\u003cbr\u003e\nCosmic Imagery, the bestselling\u003cbr\u003e\n 100 Essential Things You Didn't Know You Didn't Know,\u003cbr\u003e\n The Book of Universes, and, most recently,\u003cbr\u003e\n100 Essential Things You Didn't Know You Didn't Know About Sport.\u003cbr\u003e\n      Excerpt. © Reprinted by permission. 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