Publications-Theses

題名 JSWT+估計應用於線性迴歸變數選取之研究
Variable Selection Based on JSWT+ Estimator for Linear Regression
作者 王政忠
Wang,Jheng-Jhong
貢獻者 郭訓志
王政忠
Wang,Jheng-Jhong
關鍵詞 James-Stein估計量
變數選取
線性迴歸模型
minimax
LASSO
日期 2006
上傳時間 8-Dec-2010 14:42:50 (UTC+8)
摘要 變數選取方法已經成為各領域在處理多維度資料的工具。Zhou與Hwang在2005年,為了改善James-Stein positive part估計量(JS+)只能在完全模型(full model)與原始模型(origin model)兩者去做挑選,建立了具有Minimax性質同時加上門檻值的估計量,即James-Stein with Threshoding positive part估計量(JSWT+)。由於JSWT+估計量具有門檻值,使得此估計量可以在完全模型與其線性子集下做變數選取。我們想進一步了解如果將JSWT+估計量應用於線性迴歸分析時,藉由JSWT+估計具有門檻值的性質去做變數選取的效果如何?本文目的即是利用JSWT+估計量具有門檻值的性質,建立JSWT+估計量應用於線性迴歸模型變數挑選的流程。建立模擬資料分析,以可同時做係數壓縮及變數選取的LASSO方法與我們所提出JSWT+變數選取的流程去比較係數路徑及變數選取時差異比較,最後將我們提出JSWT+變數選取的流程對實際資料攝護腺癌資料(Tibshirani,1996)做變數挑選。則當考慮解釋變數個數小於樣本個數情況下,JSWT+與LASSO在變數選取的比較結果顯示,JSWT+表現的比較好,且可直接得到估計量的理想參數。
參考文獻 Baranchik, A.J. (1964) Multiple regression and estimation of the mean of a multivariate normal distribution. Technical Report 51, Department of Statistics, Stanford University Stanford .
Breiman, L. (1995) Better subset selection using the nonnegative garotte. Technnometrics,37,373-384
Hocking, R. R. (1976) The analysis and selection of variables in linear regression. Biometrics. 32, 1-49
Hoerl, A. E. and Kennard, R. W. (1970) Ridge regression: Biased estimation for non-orthogonal problems. Technometrics. 12,55-67
Richards, John A. (1999) An introduction James-Stein estimation
Stein, C. (1956), "Inadmissibility of the usual estimator for the mean of a multivariate distribution", Proc. Third Berkeley Symp. Math. Statist. Prob., vol. 1, at 197-206
James, W. & C. Stein (1961), "Estimation with quadratic loss", Proc. Fourth Berkeley Symp. Math. Statist. Prob., vol. 1, at 311-319
Scolve,S.L.(1968).Improved estimators for voefficients in linear regression. J. Amer. Statist. Assoc. 63,597-606
Stamey, T., Kabalin, J., McNeal, J., Johnstone, I., Freiha, F., Redwine, E. and Yang, N. (1989) Prostate specific antigen in the diagnosis and treatment of adenocarcinoma of the prostate, ii: Radical prostatectomy treated patients. J. Urol., 16, 1076-1083.
Stein, C. (1981) Estimation of the mean of a multivariate normal distribution. Ann. Statist., 9, 1135-1151.
Tibshirani, R. (1996) Regression shrinkage and selection via the lasso. J. R. Statist. Soc. B, 58, 267–288.
Zou, H. and Hastie, T (2005) Regularization and variable selection via the elastic net. J. R. Statist. Soc. B. 67, Part 2, 301–320
Zhou, H. H. and Hwang, J. T. G. (2003).Minimax estimation with thresholding. Technical report,Cornell Statistical Center.
Zhou, H. H. and Hwang, J. T. G. (2005).Minimax estimation with thresholding. And its application to wavelet analysis. The Annals of Statistics. Vol. 33, No. 1, 101–125
描述 碩士
國立政治大學
統計研究所
94354022
95
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0094354022
資料類型 thesis
dc.contributor.advisor 郭訓志zh_TW
dc.contributor.author (Authors) 王政忠zh_TW
dc.contributor.author (Authors) Wang,Jheng-Jhongen_US
dc.creator (作者) 王政忠zh_TW
dc.creator (作者) Wang,Jheng-Jhongen_US
dc.date (日期) 2006en_US
dc.date.accessioned 8-Dec-2010 14:42:50 (UTC+8)-
dc.date.available 8-Dec-2010 14:42:50 (UTC+8)-
dc.date.issued (上傳時間) 8-Dec-2010 14:42:50 (UTC+8)-
dc.identifier (Other Identifiers) G0094354022en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/49593-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 統計研究所zh_TW
dc.description (描述) 94354022zh_TW
dc.description (描述) 95zh_TW
dc.description.abstract (摘要) 變數選取方法已經成為各領域在處理多維度資料的工具。Zhou與Hwang在2005年,為了改善James-Stein positive part估計量(JS+)只能在完全模型(full model)與原始模型(origin model)兩者去做挑選,建立了具有Minimax性質同時加上門檻值的估計量,即James-Stein with Threshoding positive part估計量(JSWT+)。由於JSWT+估計量具有門檻值,使得此估計量可以在完全模型與其線性子集下做變數選取。我們想進一步了解如果將JSWT+估計量應用於線性迴歸分析時,藉由JSWT+估計具有門檻值的性質去做變數選取的效果如何?本文目的即是利用JSWT+估計量具有門檻值的性質,建立JSWT+估計量應用於線性迴歸模型變數挑選的流程。建立模擬資料分析,以可同時做係數壓縮及變數選取的LASSO方法與我們所提出JSWT+變數選取的流程去比較係數路徑及變數選取時差異比較,最後將我們提出JSWT+變數選取的流程對實際資料攝護腺癌資料(Tibshirani,1996)做變數挑選。則當考慮解釋變數個數小於樣本個數情況下,JSWT+與LASSO在變數選取的比較結果顯示,JSWT+表現的比較好,且可直接得到估計量的理想參數。zh_TW
dc.description.tableofcontents 摘要 I
謝辭 II
圖表目錄 IV
第一章 緒論 1
第二章 文獻探討 3
第三章 研究方法 5
第一節 線性迴歸模型 5
第二節 Minimax 與 Dominate 6
第三節 James-Stein type Shrinkage 7
第四節 Sclove+估計量 9
第五節 James-Stein with Thresholding估計量(JSWT) 9
第六節 JSWT+於迴歸問題之應用 12
第四章 分析結果與討論 14
第一節 模擬分析(設定真實係數三個非零) 14
第二節 模擬分析(設定真實係數僅一個非零) 21
第三節 JSWT+與LASSO參數挑選 26
第四節 攝護腺癌資料分析 27
第五章 結論與建議 29
參考文獻 31
附錄 33
(I)設定真實係數八個皆非零(0.85) 33
(II)設定真實係數八個皆為零 36
zh_TW
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dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0094354022en_US
dc.subject (關鍵詞) James-Stein估計量zh_TW
dc.subject (關鍵詞) 變數選取zh_TW
dc.subject (關鍵詞) 線性迴歸模型zh_TW
dc.subject (關鍵詞) minimaxen_US
dc.subject (關鍵詞) LASSOen_US
dc.title (題名) JSWT+估計應用於線性迴歸變數選取之研究zh_TW
dc.title (題名) Variable Selection Based on JSWT+ Estimator for Linear Regressionen_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) Baranchik, A.J. (1964) Multiple regression and estimation of the mean of a multivariate normal distribution. Technical Report 51, Department of Statistics, Stanford University Stanford .zh_TW
dc.relation.reference (參考文獻) Breiman, L. (1995) Better subset selection using the nonnegative garotte. Technnometrics,37,373-384zh_TW
dc.relation.reference (參考文獻) Hocking, R. R. (1976) The analysis and selection of variables in linear regression. Biometrics. 32, 1-49zh_TW
dc.relation.reference (參考文獻) Hoerl, A. E. and Kennard, R. W. (1970) Ridge regression: Biased estimation for non-orthogonal problems. Technometrics. 12,55-67zh_TW
dc.relation.reference (參考文獻) Richards, John A. (1999) An introduction James-Stein estimationzh_TW
dc.relation.reference (參考文獻) Stein, C. (1956), "Inadmissibility of the usual estimator for the mean of a multivariate distribution", Proc. Third Berkeley Symp. Math. Statist. Prob., vol. 1, at 197-206zh_TW
dc.relation.reference (參考文獻) James, W. & C. Stein (1961), "Estimation with quadratic loss", Proc. Fourth Berkeley Symp. Math. Statist. Prob., vol. 1, at 311-319zh_TW
dc.relation.reference (參考文獻) Scolve,S.L.(1968).Improved estimators for voefficients in linear regression. J. Amer. Statist. Assoc. 63,597-606zh_TW
dc.relation.reference (參考文獻) Stamey, T., Kabalin, J., McNeal, J., Johnstone, I., Freiha, F., Redwine, E. and Yang, N. (1989) Prostate specific antigen in the diagnosis and treatment of adenocarcinoma of the prostate, ii: Radical prostatectomy treated patients. J. Urol., 16, 1076-1083.zh_TW
dc.relation.reference (參考文獻) Stein, C. (1981) Estimation of the mean of a multivariate normal distribution. Ann. Statist., 9, 1135-1151.zh_TW
dc.relation.reference (參考文獻) Tibshirani, R. (1996) Regression shrinkage and selection via the lasso. J. R. Statist. Soc. B, 58, 267–288.zh_TW
dc.relation.reference (參考文獻) Zou, H. and Hastie, T (2005) Regularization and variable selection via the elastic net. J. R. Statist. Soc. B. 67, Part 2, 301–320zh_TW
dc.relation.reference (參考文獻) Zhou, H. H. and Hwang, J. T. G. (2003).Minimax estimation with thresholding. Technical report,Cornell Statistical Center.zh_TW
dc.relation.reference (參考文獻) Zhou, H. H. and Hwang, J. T. G. (2005).Minimax estimation with thresholding. And its application to wavelet analysis. The Annals of Statistics. Vol. 33, No. 1, 101–125zh_TW