Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 莊弘昌 | en_US |
dc.contributor.author | Chuang, Hung-Chang | en_US |
dc.contributor.author | 陳鄰安 | en_US |
dc.contributor.author | Chen Lin-An | en_US |
dc.date.accessioned | 2014-12-12T02:17:11Z | - |
dc.date.available | 2014-12-12T02:17:11Z | - |
dc.date.issued | 1996 | en_US |
dc.identifier.uri | http://140.113.39.130/cdrfb3/record/nctu/#NT850337007 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/61733 | - |
dc.description.abstract | 我們導出線性迴歸模型及聯立方程式模型的Mallows形式有界迴歸 分位向 量之近似分配。我們也做蒙地卡羅(Monte Carlo)模擬,並比 較均方誤差且 驗證出如果獨立變數產生毛差(gross errors)時,則有界 迴歸分位向量將比無界迴歸分位 向量(見Koenker及Bassett(1978))來得 有效率 。 We present asymptotic distributions of the Mallows type bounded-influencereg ression quantile for the linear regression model and also the simultaneousequa tions model. Monte Carlo simulation comparing mean squared errors showsthat th e bounded-influence one is more efficient than the unbounded- influence one(Koe nker and Bassett(1978))when gross errors occur in the independent-variables-s pace. | zh_TW |
dc.language.iso | zh_TW | en_US |
dc.subject | 影響 | zh_TW |
dc.subject | 迴歸分位向量 | zh_TW |
dc.subject | influence | en_US |
dc.subject | regression quantile | en_US |
dc.title | 線性迴歸模型及聯立方程式模型之Mallows形式有界迴歸分位向量 | zh_TW |
dc.title | Mallows Type Bounded Influence Regression Quantile for Linear Regression Model and Simultaneous Equations Model | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | 統計學研究所 | zh_TW |
Appears in Collections: | Thesis |