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    政大機構典藏 > 商學院 > 統計學系 > 學位論文 >  Item 140.119/112618
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    題名: 基於LASSO和FORWARD的節點選取方法比較
    A comparison between two knot selection methods based on LASSO and FORWARD selection
    作者: 孟耿德
    Meng, Geng De
    貢獻者: 黃子銘
    Huang, Tzee Ming
    孟耿德
    Meng, Geng De
    關鍵詞: 變數選取
    最小壓縮法
    KNOT
    LASSO
    日期: 2017
    上傳時間: 2017-09-13 14:12:10 (UTC+8)
    摘要: 在無母數迴歸問題中,如果迴歸函數以spline函數近似,而且使用等距節點,則節點選取可以視為一個變數選取的問題。TiBshirani(1996)提出最小絕對壓縮挑選運算(Least Absolute Shrinkage and Selection Operator; LASSO)能夠對變數縮減,本研究中將考慮使用LASSO和forward 兩種選取變數方法進行節點選取。根據本研究模擬結果,forward選取方法的挑選節點效果比較好。
    In nonparametric regression, if the regression function is approximated using a spline function with equally spaced knots ,then the problem of knot selection can Be considered as a variable selection problem. Tibshirani(1996) proposed Least Absolute Shrinkage and Selection Operator(LASSO), which can Be used for variable selection. In this thesis, two variable selection methods: LASSO and forward, are considered for knots selection. According to the simulation results in this thesis, the forward method is better for knot selection.
    參考文獻: 參考文獻

    [1]Charles J. Stone(1997)Polynomial Splines and their Tensor Products in Extended Linear Modeling;p1374-p1377
    [2]Denison, D., Mallick, B., and Smith, A. (1998). Automatic Bayesian curve fitting, J. R. Statist. Soc., B, 60, 333–350
    [3]EuBank, R.L. (1988). Smoothing Splines and Non-parametric Regression, Marcel Dekker, New Yorkand Base
    [4 ]Hoerl, A. E. and Kennard, R. W. (1970). Ridge regression: Biased estimation for nonorthogonal proBlems. Technometrics 12, 55-67.
    [5]I. J. SchoenBerg, On trigonometric spline interpolation, J. Math. Mech. 13(1964), 795-825
    [6]Michael R. OsBorne, Brett Presnell, and Berwin A. Turlach. Knot selection for regression splines via the LASSO. In Computing Science and Statistics. Dimen-sion Reduction, Computational Complexity and Information. Proceedings of the 30th Symposium on the Interface, pages 44–49, 1998
    [7]WahBa, G. (1990) Spline Models for OBservational Data.
    [8] R. TiBshirani. Regression shrinkage and selection via the LASSO. Journal of the RoyalStatistical Society (Series B), 58:267–288, 1996.
    [9 ] Schumaker, L. L. (1981) Spline functions, Wiley, New York.
    描述: 碩士
    國立政治大學
    統計學系
    104354029
    資料來源: http://thesis.lib.nccu.edu.tw/record/#G1043540291
    資料類型: thesis
    顯示於類別:[統計學系] 學位論文

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