English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 113656/144643 (79%)
Visitors : 51714234      Online Users : 580
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/84726


    Title: 二群多變量時間數列間之簡化因果關係
    Other Titles: A Trimmed Causal Relationship between Two Groups of Multivariate Time Series Data
    Authors: 洪英超
    Contributors: 統計學系
    Keywords: Granger領先;向量自我迴歸過程;顯著變數;預測;前進選擇法
    Granger causality;Vector Autoregressive Process;significant variables;forecasting;forward selection
    Date: 2012
    Issue Date: 2016-04-15 09:52:36 (UTC+8)
    Abstract: 本計畫將探討”驗證二群多變量時間數列因果關係”中之變數選擇問題。其想法主要是 利用所謂的”向量自我迴歸模型”(Vector Autoregression Model) 將二群多變量時間數 列中的”重要變數”萃取出來,並藉此建構一簡化(且新)的”因果關係。當向量自我迴 歸模型的參數已知時,我們將証明此一變數選擇問題的解可以完全的表達出來。 當向 量自我迴歸模型的參數未知時,我們將介紹一個統計的假設檢定程序來估計(或近似) 此一變數選擇問題的解。
    In this project we investigate a variable selection problem in the validation of causal relationship between two groups of multivariate time series data. By utilizing the Vector Autoregression (VAR) model, we introduce how to extract “significant variables” in both groups of time series data so that a “trimmed causal relationship” can be presented based on precedence and predictability. When the parameters of the VAR model are known, we show that explicit conditions for solving this variable selection problem can be obtained; when the parameters are unknown, a statistical hypothesis testing procedure is used to approximate the solution.
    Relation: 計畫編號 NSC101-2118-M004-002
    Data Type: report
    Appears in Collections:[新聞學系] 國科會研究計畫

    Files in This Item:

    File Description SizeFormat
    101-2118-M004-002.pdf3716KbAdobe PDF2361View/Open


    All items in 政大典藏 are protected by copyright, with all rights reserved.


    社群 sharing

    著作權政策宣告 Copyright Announcement
    1.本網站之數位內容為國立政治大學所收錄之機構典藏,無償提供學術研究與公眾教育等公益性使用,惟仍請適度,合理使用本網站之內容,以尊重著作權人之權益。商業上之利用,則請先取得著作權人之授權。
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    2.本網站之製作,已盡力防止侵害著作權人之權益,如仍發現本網站之數位內容有侵害著作權人權益情事者,請權利人通知本網站維護人員(nccur@nccu.edu.tw),維護人員將立即採取移除該數位著作等補救措施。
    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback