博碩士論文 982205008 完整後設資料紀錄

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DC.contributor統計研究所zh_TW
DC.creator吳嘉洋zh_TW
DC.creatorJia-Yang Wuen_US
dc.date.accessioned2011-7-4T07:39:07Z
dc.date.available2011-7-4T07:39:07Z
dc.date.issued2011
dc.identifier.urihttp://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=982205008
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.abstract失業率關係到一個國家的經濟而且也受到全球經濟的影響。多維時間序列也被用來處理多個國家之間的失業率。在建立多維時間序列模型的時候,我們應該考慮在每個邊際時間序列之間一個比較彈性的相關結構。近年來,copula模型在高維度的相關結構建模中提供了一個比較彈性的架構。在本篇論文中,我們考慮兩中邊際時間序列,包含white noise 和GARCH。接著,我們用不同的copula去連結這些時間序列,包括有Gaussian copula和三個比較普遍的Archimedean copulas。最後, 我們透過模擬去論證我們的模型以及用台灣日本和美國的失業率去做實例分析。 zh_TW
dc.description.abstractThe unemployment rate is related to the economics of its own country and also influenced by global economics. Multivariate time series are used for modeling unemployment rates among different countries. When modeling multivariate time series, a more flexible dependence structure among each marginal time series should be considered. Recently, the copula model provides a flexible framework for modeling high dimensional dependence structure. In this thesis, we consider two marginal time series, including the simple white noise and the generalized autoregressive conditional heteroskedasticity (GARCH). Then, we merge these time series by a variety of copulas, including the Gaussian copula and three popular Archimedean copulas. Finally, we demonstrate our models through simulation studies and a real data analysis using unemployment rates of Taiwan, Japan, and the United States. en_US
DC.subjectGARCHzh_TW
DC.subjectwhite noisezh_TW
DC.subjectArchimedean copulaszh_TW
DC.subjectGaussian copulazh_TW
DC.subjectGARCHen_US
DC.subjectwhite noiseen_US
DC.subjectArchimedean copulasen_US
DC.subjectGaussian copulaen_US
DC.titleCopula連結時間序列應用在失業率下之建模zh_TW
dc.language.isozh-TWzh-TW
DC.titleCopula-Based Time Series with Applications to UnemploymentRates Modelingen_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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