博碩士論文 100225011 完整後設資料紀錄

DC 欄位 語言
DC.contributor統計研究所zh_TW
DC.creator鄭雅云zh_TW
DC.creatorCHENG, YA-YUNen_US
dc.date.accessioned2013-7-11T07:39:07Z
dc.date.available2013-7-11T07:39:07Z
dc.date.issued2013
dc.identifier.urihttp://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=100225011
dc.contributor.department統計研究所zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstractLyles et al. (2007)提出一個針對廣義線性模型,利用資料擴充來估計統計檢定力的方法。由於此方法需要假設反應變數的分配,再利用費雪訊息矩陣估計變異數矩陣,並利用Wald 檢定統計量之漸進分佈估計統計檢定力。但當模型假設錯誤時,所得到的費雪訊息矩陣基本上是不正確的。本文之目的在於利用拔靴法來估計當模型假設錯誤時正確的變異數矩陣,再利用Wald 檢定統計量之漸進分佈估計出正確的統計檢定力。zh_TW
dc.description.abstractLyles et al. (2007) proposed an expanded data set method for calculating testing power in the setting of generalized linear models. This approach requires the Fisher information matrix in order to evaluate the Wald test statistic. We recommend using the Bootstrap methodology to calculate a robust version of the Fisher information matrix which remains legitimate under model misspecification. Hence, one can estimate the power of the test statistics without making distributional assumptions.en_US
DC.subject廣義線性模型zh_TW
DC.subject擴充資料集zh_TW
DC.subject統計檢定力zh_TW
DC.subject費雪訊息zh_TW
DC.subjectWald 檢定統計量zh_TW
DC.subject拔靴法zh_TW
DC.subjectgeneralized linear modelen_US
DC.subjectexpanded data seten_US
DC.subjectpoweren_US
DC.subjectFisher informationen_US
DC.subjectWald test statisticen_US
DC.subjectBootstrapen_US
DC.title針對名目、個數與有序資料迴歸係數統計檢定力計算的普世強韌法zh_TW
dc.language.isozh-TWzh-TW
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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