串行事件資料的條件模型

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DC Field	Value	Language
dc.contributor.author	何杰翰	zh_TW
dc.contributor.author	王維菁	zh_TW
dc.contributor.author	Ho, Chieh-Han	en_US
dc.contributor.author	Wang, Wei-Jing	en_US
dc.date.accessioned	2018-01-24T07:39:56Z	-
dc.date.available	2018-01-24T07:39:56Z	-
dc.date.issued	2017	en_US
dc.identifier.uri	http://etd.lib.nctu.edu.tw/cdrfb3/record/nctu/#GT070452602	en_US
dc.identifier.uri	http://hdl.handle.net/11536/140942	-
dc.description.abstract	串行事件資料在醫學領域是相當常見的。在此篇論文中，我們探討如何利用第一段間隔時間去對第二段間隔時間建模。我們討論了些建模的方法，並藉由模擬評各個方法的可行性，除此之外，也提出各方法資料生成的演算法。	zh_TW
dc.description.abstract	Serial events data are commonly seen in medical applications. In this thesis, we investigate how to utilize the information of the first gap time to model the second gap time. We discuss several modeling strategies and evaluate their validity via simulations. We also propose data generation algorithms for the proposed models.	en_US
dc.language.iso	en_US	en_US
dc.subject	條件模型	zh_TW
dc.subject	復發資料	zh_TW
dc.subject	串行事件資料	zh_TW
dc.subject	conditional modeling	en_US
dc.subject	recurrence data	en_US
dc.subject	serial events data	en_US
dc.title	串行事件資料的條件模型	zh_TW
dc.title	Conditional Modeling for Serial Events Data	en_US
dc.type	Thesis	en_US
dc.contributor.department	統計學研究所	zh_TW
Appears in Collections:	Thesis