| dc.contributor.advisor | 黃子銘 | zh_TW |
| dc.contributor.advisor | Huang, Tzee Ming | en_US |
| dc.contributor.author (作者) | 孟耿德 | zh_TW |
| dc.contributor.author (作者) | Meng, Geng De | en_US |
| dc.creator (作者) | 孟耿德 | zh_TW |
| dc.creator (作者) | Meng, Geng De | en_US |
| dc.date (日期) | 2017 | en_US |
| dc.date.accessioned | 13-九月-2017 14:12:10 (UTC+8) | - |
| dc.date.available | 13-九月-2017 14:12:10 (UTC+8) | - |
| dc.date.issued (上傳時間) | 13-九月-2017 14:12:10 (UTC+8) | - |
| dc.identifier (其他 識別碼) | G1043540291 | en_US |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/112618 | - |
| dc.description (描述) | 碩士 | zh_TW |
| dc.description (描述) | 國立政治大學 | zh_TW |
| dc.description (描述) | 統計學系 | zh_TW |
| dc.description (描述) | 104354029 | zh_TW |
| dc.description.abstract (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。 | zh_TW |
| dc.description.abstract (摘要) | 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. | en_US |
| dc.description.tableofcontents | 第一章 緒論 1 第二章 文獻迴顧 3 第三章 研究方法 4 第一節 模型假設與節點對應變數關係 4 第二節 LASSO運算 5 第四章 模擬和比較 7 第一節 節點設定 7 第二節 模擬比較 10 第五章 結論與建議 11 | zh_TW |
| dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G1043540291 | en_US |
| dc.subject (關鍵詞) | 變數選取 | zh_TW |
| dc.subject (關鍵詞) | 最小壓縮法 | zh_TW |
| dc.subject (關鍵詞) | KNOT | en_US |
| dc.subject (關鍵詞) | LASSO | en_US |
| dc.title (題名) | 基於LASSO和FORWARD的節點選取方法比較 | zh_TW |
| dc.title (題名) | A comparison between two knot selection methods based on LASSO and FORWARD selection | en_US |
| dc.type (資料類型) | thesis | en_US |
| dc.relation.reference (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. | zh_TW |
