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Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/87950
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dc.contributor.advisor姜志銘zh_TW
dc.contributor.advisorJiang, Zhi Mingen_US
dc.contributor.author劉士榮zh_TW
dc.contributor.authorLiu, Shi Rongen_US
dc.creator劉士榮zh_TW
dc.creatorLiu, Shi Rongen_US
dc.date1995en_US
dc.date.accessioned2016-04-29T01:39:39Z-
dc.date.available2016-04-29T01:39:39Z-
dc.date.issued2016-04-29T01:39:39Z-
dc.identifierB2002003046en_US
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/87950-
dc.description碩士zh_TW
dc.description國立政治大學zh_TW
dc.description應用數學系zh_TW
dc.description.abstract以貝氏方法處理部分區分（partially-classified）失去部分訊息資料的類別抽樣（categorical sampling with censored data）的研究已行之有年，但大部分都在“失去部分訊息但無價值性”（non-informative censoring）以及“誠實回答”（truthful reporting）的前提下。Thomas J. Jiang取消以上二個限制，於1995年提quasi-Bayes method來近似這類問題的貝氏解。而Paulino and Pereira亦於1995年提出另一方法求得貝氏解。本文重點在於比較此二種方法，亦探討Thomas J. Jiang之quasi-Bayes method之收斂性。zh_TW
dc.description.abstractBayesian treatments of categorical sampling with censored （partially-classified）data have been subjected to research for decades, but most of these researches focused on the analysis of categorical date under non-informative censoring and truthful reporting Thomas J. Jiang dropped these assumptions and proposed quasi-Bayes method to approximate a coherent Bayes solution in 1995. Paulino and Pereira also proposed another method to get Bayes solution In the paper, we shall compare these two methods and study the convergence of quasi-Bayes method..........en_US
dc.description.tableofcontents1.簡介……….2\r\n2.Two Bayesian approaches……….3\r\n2.1qausi-Bayes method..........3\r\n2.2Paulino and Pereira’s approach..........9\r\n3.quasi-Bayes method之模擬結果..........14\r\n4.Quasi-Bayes method與Paulino and Pereira’s method之比較..........25\r\n5.結論..........31\r\nReference..........32zh_TW
dc.source.urihttp://thesis.lib.nccu.edu.tw/record/#B2002003046en_US
dc.title對失去部分訊息而有價值的類別資料的貝氏方法之探討zh_TW
dc.titleA study on Bayesian methods for categorical data under informative censoringen_US
dc.typethesisen_US
dc.relation.referenceBasu, D., and Pereira, C. A. B. (1982), \" On the Bayesian Analysis of Categorical Data:The Problem of Nonresponse,\" Journal of Statistical Planning and Inference, 6,\r\n345-362.\r\nDickey, J. M., Jiang, J. M., and Kadane, J. B. (1987), \" Bayesian Methods for\r\nCensored Categorical Data,\" Journal of the American Statistical Association, 82,\r\n773-781.\r\nJiang, T. J., Kadane, J. B., and Dickey, J. M. (1992), \" Computation of Carlson`s\r\nMultiple Hypergeometric Function R for Bayesian Applications,\" Jornal of\r\nComputation and Graphical Statistics. 1,231-251.\r\nJiang, T. J., (1995). \" Quasi-Bayes Sequential Method for Categorical Data Under\r\nInformative Censoring,\" Technical Report, To be submitted for Publication.\r\nKarson, M. J., and Wrobleski, W. 1. (1970), \" A Bayesian Analysis of Binomial Data\r\nwith a Partially Informative Category,\" in Proceedings of the Business and\r\nEconomics Statistics, American Statistical Association. 532-534.\r\nLittle, R. 1. A, and Rubin, D. B. (1987), \"Statistical Analysis with Missing Data,\" New York, John Wiley? Sons.\r\nMakov, U. E., and Smith, A F. M. (1977), \" A Quasi-Bayes Unsupervised Learning\r\nProcedures for Priors,\" IEEE Trans. In! Theory, IT-23, 761-764.\r\nPaulino, C. D. M. (1991), \" Analysis of Incomplete Categorical Data : A Survey of the Conditional Maximum Likelihood and Weighted Least Squares Approaches,\"\r\nBrazilian J. Prob. Statist. 5, 1-42.\r\nPaulino, C. D. M., and Pereira, C. A. B. (1992), \" Bayesian Analysis of Categorical\r\nData Informatively Censored,\" Commun. Statist. A 21,2689-705.\r\nPaulino, C. D. M., and Pereira, C. A. B. (1995), “Bayesian Methods for Categorical\r\nData Under Informative General Censoring,\" Biometrika, 82, 2, pp. 439-46.\r\nSmith, A. F. M., and Makov, U. E. (1978), \" A Quasi-Bayes Sequential Procedure for\r\nMixture,\" Journal of the Royal Statistical Society, Ser. B. 40, 106-112.zh_TW
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