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Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/36397
DC FieldValueLanguage
dc.contributor.advisor姜志銘zh_TW
dc.contributor.advisorJiang,Thomsa J.en_US
dc.contributor.author柯力文zh_TW
dc.contributor.authorKo, Li-wenen_US
dc.creator柯力文zh_TW
dc.creatorKo, Li-wenen_US
dc.date2002en_US
dc.date.accessioned2009-09-18T10:28:34Z-
dc.date.available2009-09-18T10:28:34Z-
dc.date.issued2009-09-18T10:28:34Z-
dc.identifierG0090751004en_US
dc.identifier.urihttps://nccur.lib.nccu.edu.tw/handle/140.119/36397-
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.description90751004zh_TW
dc.description91zh_TW
dc.description.abstract以貝氏方法來處理部分區分(partially-classified)或是失去部分訊息資料的類別抽樣(categorical sampling with censored data)，大部分建立在「誠實回答」(truthful reporting)以及「無價值性失去部分訊息」(non-informative censoring)的前提下。Dr.Jiang(1995)取消以上兩個限制，提出quasi-Bayes method來近似這類問題的貝氏解。另外我們也嘗試利用Gelfand and Smith(1990)針對Gibbs sampler所提出的收斂方法來估計。本文重點在比較此兩種方法的估計值準確性，並考慮先驗參數(prior)對估計精準的影響。zh_TW
dc.language.isoen_US-
dc.source.urihttp://thesis.lib.nccu.edu.tw/record/#G0090751004en_US
dc.subjectquasi-Bayesen_US
dc.subjectGibbsen_US
dc.subjectcensored dataen_US
dc.titleA comparison between quasi-Bayes method and Gibbs sampler on the problem with censored datazh_TW
dc.typethesisen
item.fulltextWith Fulltext-
item.grantfulltextopen-
item.languageiso639-1en_US-
item.openairecristypehttp://purl.org/coar/resource_type/c_46ec-
item.cerifentitytypePublications-
item.openairetypethesis-
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