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    政大機構典藏 > 理學院 > 應用數學系 > 學位論文 >  Item 140.119/29675
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/29675


    Title: 模糊樣本之區間迴歸分析
    Authors: 陳孝煒
    Contributors: 吳柏林
    陳孝煒
    Keywords: 模糊迴歸參數區間估計
    最小平方法
    區間模糊數距離
    Date: 2006
    Issue Date: 2009-09-11 16:01:55 (UTC+8)
    Abstract: 傳統的迴歸是假設觀測值的不確定性來自於隨機,模糊迴歸則是假設不確定性來自多重隸屬現象。一般的模糊迴歸採用樣本模糊數 來對模糊迴歸參數進行估計,其中 為觀測模糊數, 依舊為實數值。我們認為 的假設不能真實地表達出樣本所蘊含的資訊,本研究將假設 也為模糊數,如此一來對樣本的解釋方式將更為貼近現實,且估計的過程則採用通用的最小平方估計,保留迴歸原始精神但是在模糊數上則有更深入的探究。迴歸常用來建構經濟和財務的模型,而此種模型經常帶有模糊的特質,例如景氣循環、不規則趨勢等。在本文中也會舉出例子來輔助說明此研究的實用性。

    關鍵字:模糊迴歸參數區間估計、最小平方法、區間模糊數距離
    Reference: [1]吳柏林,(1999)。現代統計學,252-255。台北:五南書局
    [2]吳柏林¸楊文山 (1997). 模糊統計在社會調查分析的應用. 社會科學計量方法發展與應用. 楊文山主編:中央研究院中山人文社會科學研究所.
    [3]吳柏林(2005).模糊統計導論方法與應用。台北,五南圖書出版社。
    [4]陳雲岫,蔡敏盛,(1998),模糊迴歸分析穩健性之探討- 以二階線性為例.中國工業工程學會論文集,中華民國八十七年度,pp.1034-1039,1998年12月.
    [5]阮亨中、吳柏林,(2000)。模糊數學與統計應用, 233-250; 319-341。台北:俊傑書局。
    [6]Wu, B. and Tseng, N. (2002). A new approach to fuzzy regression models with application to business cycle analysis. Fuzzy Sets and System. 130,33-42.
    [7]Yang, M. and Ko, C. (1997). On cluster-wise fuzzy regression analysis. IEEE Trans. Systems
    Man Cybernet, vol27,1-13.
    [8]Savic, D.A. and Pedrycz, W. (1991). Evaluation of Fuzzy Linear Regression Models. Fuzzy Set and Systems, 23, 51-63.
    [9]Tanaka, H., Uejima, S. and Asai, K. (1980). Fuzzy Linear Regression Model. International Congress on Applied Systems Research and Cybernetics. Aculpoco, Mexico.
    [10]Tanaka, H., Uejima, S. and Asai, K. (1982). Linear Regression Analysis with Fuzzy model. IEEE Trans. SystemsMan Cybernet, vol SMC 12, 903-907.
    [11]Tanaka, H., & Ishibuchi, H. (1993). An architecture of neural networks with interval weights and its application to fuzzy regression analysis. Fuzzy Sets and Systems, 57, 27-39.
    [12] Wang, H. F. and R. C. Tsaur, “Bi-criteria variable selection in fuzzy regression equation,” Computers and Mathematics with Applications, 40, 877-883(2000)..
    [13] Tanaka, H. and J. Watada, “Possibility linear systems and their application to the linear regression model,”Fuzzy Sets and Systems, 27, 275-289 (1988).
    [14] H. Tanaka, S. Vejima, K. Asai, Linear regression analysis with fuzzy model, IEEE Trans. Syst. Man, Cybernetics, Jun, 1982.
    [15] P. Diamond . Fuzzy least squares. Information Science 46 (1998)
    Description: 碩士
    國立政治大學
    應用數學研究所
    93751014
    95
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0093751014
    Data Type: thesis
    Appears in Collections:[應用數學系] 學位論文

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