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Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/32608
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dc.contributor.advisor姜志銘zh_TW
dc.contributor.author羅文宜zh_TW
dc.creator羅文宜zh_TW
dc.date2004en_US
dc.date.accessioned2009-09-17T05:50:26Z-
dc.date.available2009-09-17T05:50:26Z-
dc.date.issued2009-09-17T05:50:26Z-
dc.identifierG0927510061en_US
dc.identifier.urihttps://nccur.lib.nccu.edu.tw/handle/140.119/32608-
dc.description碩士zh_TW
dc.description國立政治大學zh_TW
dc.description應用數學研究所zh_TW
dc.description92751006zh_TW
dc.description93zh_TW
dc.description.abstract對於處理部份區分或是失去部分訊息資料的類別抽樣的問題，在許多領域裡皆有許多的應用。貝氏方法雖可處理這類問題，但是貝氏方法對這類問題的計算相當耗時，因此對於這種問題的後驗估計，Jiang (1995) 及 Jiang and Dickey (2005) 提出quasi-Bayes方法，Jiang and Ko (2004)利用Gibbs sampler來近似(approximate)這些後驗估計值。但是這兩種近似方法的優劣，因為貝氏方法計算上的困難，一直沒有任何文章作這方面的比較，本文突破計算上的某些限制，在小樣本時，對這兩種近似方法的近似度(相對於真正的貝氏值)作比較，進一步探討使用兩種比較方法的優劣。zh_TW
dc.description.tableofcontents1 簡介........................................................3\n2 計算方法的介紹..............................................4\n 2.0 貝氏法在不完整多元伯努利上的應用.........................4\n 2.1 準貝氏法在不完整多元伯努利上的應用.......................8\n 2.2 吉氏取樣器..............................................11\n 2.2.1 吉氏取樣器的介紹.....................................11\n 2.2.2 簡單的收斂說明.......................................13\n 2.2.3 吉氏取樣器在不完整多元伯努利上的應用.................15\n3 Fortran程式................................................18\n 3.1 迴圈單一化..............................................18\n 3.2 溢位....................................................21\n4 準貝氏法與吉氏取樣器的比較結果.............................27\n5 結論.......................................................41\nA 兩種比較方法之平均相對誤差的折線圖.........................44\nB 兩種比較方法在觀察值order不同時估計值的MSE折線圖...........48\nC Fortran 90程式.............................................50zh_TW
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dc.language.isoen_US-
dc.source.urihttp://thesis.lib.nccu.edu.tw/record/#G0927510061en_US
dc.subject遺失資料zh_TW
dc.subject貝氏方法zh_TW
dc.subject準貝氏法zh_TW
dc.subject吉氏取樣器zh_TW
dc.title具有訊息的遺失資料計算方法之比較zh_TW
dc.typethesisen
dc.relation.referenceCasella. G., and George, E. I. (1992), \"Explaining the Gibbs sampler,\" The American Statistician, 46, 167-174.zh_TW
dc.relation.referenceDickey, J.M., Jiang, T. J., and Kadane, J. B. (1987), \"Bayes Methods for Censored Categorical Data,\" Journal of the American Statistical Association, 85, 398-409.zh_TW
dc.relation.referenceGelfand, A. E., Smith, A. F. M. (1990), \"Sampling-Based Approaches to Calculating Marginal Densities,\" Journal of the American Statistical Association, 85, 398-409.zh_TW
dc.relation.referenceHastings, W. K. (1970), \"Monte Carlo Sampling Methods Using Markov Chains and their Application,\" Biometrika, 57, 97-109.zh_TW
dc.relation.referenceJiang, T. J. (1995), \"Quasi-Bayes Sequential Method For Categorical Data Under Informative Censoring,\" Technical Report, 1995-02, Dept. of Mathematical Sciences, National Chengchi University.zh_TW
dc.relation.referenceJiang, T. J., and Dickey, J. M. (2005), \"Quasi-Bayes Methods for Categorical Data Under Informative Censoring,\" to be published.zh_TW
dc.relation.referenceJiang, T. J., Kadane, J. B., and Dickey, J. M. (1992), \"Computation of Carlson`s Multiple Hypergeometric Function R for Bayesian Applications,\" Journal of Computational and Graphical Statistics, 1, 231-251.zh_TW
dc.relation.referenceJiang, T. J., and Ko, Li-Wen (2004), \"The Gibbs sampler for Bayesian Analysis on Censored Categorical Data,\" 2004 Proceeding of the section on Bayesian Statistical Science of the American Statistical Association, 97-103.zh_TW
dc.relation.referenceKarson, M. J., and Wrobleski, W. J. (1970), \"A Bayesian Analysis of Binomial Data With a Partially Informative Category,\" in Proceedings of the Business and Economic Statistics Section, American Statistical Association, 532-534.zh_TW
dc.relation.referenceGeman, S., and Geman, D. (1984), \"Stochastic Relation, Gibbs Distribution and the Bayesian Restortion of Image,\" IEEE Transactions on Pattern Analysis and Machine Intelligence, 6, 721-741.zh_TW
dc.relation.reference汪為開(1995), \"失去部分訊息而有價值的類別資料依循序程序處理之計算方法\"碩士論文-國立政治大學應用數學系研究所.zh_TW
dc.relation.reference柯力文(2003), \"準貝氏法與吉氏取樣器在處理失去部分訊息資料上的比較\" 碩士論文-國立政治大學應用數學系研究所.zh_TW
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