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題名 改良式脊迴歸分析法於預測模式之應用
Applied Improved Ridge Regression Analysis作者 周玫芳
Chou, Mei Fang貢獻者 謝邦昌
Shia, Ben Chang
周玫芳
Chou, Mei Fang關鍵詞 脊迴歸
刀削法
偏量估計式
Ridge Regression
Jackknife
Biased estimator日期 1994
1993上傳時間 29-四月-2016 15:31:04 (UTC+8) 摘要 當我們在應用迴歸分析法時，往往會遇到兩個或多個自變數間存在著線性 參考文獻 1.林燦隆、謝邦昌、唐榮澤，(1989)，利用氣象因子建立甘蔗糖份含量之預測模式，台灣糖業研究所研究彙報，124:1-122.鄭敏祿，(1985)，脊廻歸估計之模擬研究。國立政治大學統計學研究所碩士論文。3.謝邦昌，(1991)，綜合預測模式之探討－甘蔗蔗產量及糖份含量依氣象因子二段式加權預測模式之研究。國立台灣大學農藝學研究所生物統計組博士論文。4. Brown, W.G. and Beattie, B.R. (1975).Improving Estimates Of Economic Parameters By Use Of Ridge Regression With Production Function Applications. Am.J.Agric.Econ.,57,21-325. Douglas, G.F.(1978).Ridge Regression:When Biased Estimation Is Better, Social Science Ouarterly, Vol.58,No.4,March: 708-7166. Draper, N. R. and Smith , H. (1981). Applied Regression Analysis, Second Edition, New York. 7.Ellen ,B.R.(1991). Prediction Error and Its Estimation for Subset-Selected Models, Technometrics, Vol.33, No.4,November:459-4678.Hinkley, D.V. (1977). Jackknifing In Unbalanced Situations, Technometrics, Vol.19,No.3,August:285-2929.Hoerl, A.E. and Kennard, R.W. (1970). Ridge Regression : Biased Estimation For Nonorthogonal Problems, Technometrics, Vol.12, No.1, February:55-6710. Hoerl, A.E. and Kennard, R.W. (1970). Ridge Regression : Applications to Nonorthogonal Problems , Technometrics, Vol.12, No.1, February:69-8311. Hoerl, A.E. Kennard, R.W. and Baldwin,K.F.(1975) Ridge Regression: Some Simulations, Communications In Statistics, 4(2), 105-12312.Hoerl,A.E. and Kennard,R.W.(1976).Ridge Regression : Iterative Estimation Of The Biased Parameter, Commun.Statis. Theor. Meth.A5(1):77-8813.John Neter, (1989). Applied Linear Regression Models, Second Edition, Boston.14.Loesgen,K.H.(1990). Generalization and Bayesian Interpretation of Ridge-Type Estimators with Good Prior Means, Statistical Papers, 31:147-15715.McDonald ,G.C. and Galarneau,D.I. (1975). A Monte Carlo evaluation of Some Ridge Type estimators.JASA,70:407-41616.Miller,R.G. (1968) Jackkinfing Variance. Ann.Math.Stqtist.,39:567-58217.Miller,R.G. (1974). An Unbalanced Jackknife, The Annals Of Statistics, Vol 2, No.5:880-89118.Nityananda Sarkar, (1992), A New Estimator Combining The Ridge Regression And The Restricted Least Squares Methods Of Estimation, Commun. Statist. Theory Meth.,21(7):1987-200019.Nordberg, L. (1982). A Procedure For Determination Of A Good Ridge Parameter In Linear Regression. Commun. Statist. B11:285-30920.Quenouille,M.H.(1956).Note On Bias In Estimation. Biometrika. 43:353-36021.SAS/IML User’s Guide.(1985). SAS Institute Inc. North Carolina.22.Segerstedt,B.(1992).On Ordinary Ridge Regression In Generalized Linear Models, Commun.Statist.-Theory Meth., 21(8):2227-224623.Shao,J. and Wu,C.F.J. (1987), Heterpscedastocoty-Robustness Of Jackknife Variance Estimators In Linear Models, The Annals Of Statistics, Vol.15 ,No. 4:1563-157924.Shao,J.(1992).Jackknifing In Generalized Linear Models, Ann.Inst. Statist. Math. Vol.44,No. 4,673-68625. Turkey, J.W. (1958) Bias And Confidence In Not-Quite Large Samples. Ann.Math.Statist.,29:614 描述 碩士
國立政治大學
統計學系
81354014資料來源 http://thesis.lib.nccu.edu.tw/record/#B2002003827 資料類型 thesis dc.contributor.advisor 謝邦昌 zh_TW dc.contributor.advisor Shia, Ben Chang en_US dc.contributor.author (作者) 周玫芳 zh_TW dc.contributor.author (作者) Chou, Mei Fang en_US dc.creator (作者) 周玫芳 zh_TW dc.creator (作者) Chou, Mei Fang en_US dc.date (日期) 1994 en_US dc.date (日期) 1993 en_US dc.date.accessioned 29-四月-2016 15:31:04 (UTC+8) - dc.date.available 29-四月-2016 15:31:04 (UTC+8) - dc.date.issued (上傳時間) 29-四月-2016 15:31:04 (UTC+8) - dc.identifier (其他 識別碼) B2002003827 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/88359 - 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) 81354014 zh_TW dc.description.abstract (摘要) 當我們在應用迴歸分析法時，往往會遇到兩個或多個自變數間存在著線性 zh_TW dc.description.tableofcontents 第 一 章 緒論1-1 研究緣起………………………………………………………………………………………………………….11-2 研究動機與目的……………………………………………………..……………………………………….21-3 研究方法及架構…………………………..………………………………………………………………….8第 二 章 前人研究2-1 脊迴歸方面之文獻探討………………………………………………………………….…….………….92-2 Jackknife估計法之文獻探討…………………………………………………….……………….….112-3 改良式脊迴歸分析法之文獻探討……………………………………………….………………….13第 三 章 理論方法3-1 脊迴歸分析……………………………………………………………………………….…………………….143-2 Jackknife取一法………………………………………………..………………………………………….233-3 改良式脊迴歸估計法……………………………………………………………….…………………….29第 四 章 實例探討與模擬研究4-1 實例探討…………………………………………………………………………….………………….……….344-2 電腦模擬………………………………………………………………………….…………………….……….384-3 模擬結果……………………………………………………………………….……………………….……….41第 五 章 結論………………………………………….…………………………………….…………….53參考文獻……………………………………………………………………………………..……………..………….56附錄一 SAS/IML程式……………………………………….……..…………………………………….59附錄二 實例探討之原始資料及輸出結果…………………………………………………….62表目錄表 一 傳統脊估式與改良式脊估式預測能力之比較……………………..…………..………35表 二 Jackknife取一法n個估計系數………………………………………………………….………36表 三 r² = 0.1傳統脊估式與改良式脊估式之比較分析………………..…………..………43表 四 r² = 0.3傳統脊估式與改良式脊估式之比較分析……………………..……..………44表 五 r² = 0.5傳統脊估式與改良式脊估式之比較分析…………………………....………45表 六 r² = 0.7傳統脊估式與改良式脊估式之比較分析……………………..……..………46表 七 r² = 0.9傳統脊估式與改良式脊估式之比較分析………..……………….….………47表 八 傳統脊估式與改良式脊估式之比較分析……………………………….…………………48圖目錄圖 一 bR 與b之抽樣分配……………………………………………………………………………………14圖 二 傳統脊估式與改良式脊估式的預測情形……………………………………….…………35圖 三 r² = 0.1 Td²與I d²之比較……………………………………………………..………………………49圖 四 r² = 0.3 Td²與I d²之比較………………………………………..……………………………………49圖 五 r² = 0.5 Td²與I d²之比較…………………………………………………………………………..…50圖 六 r² = 0.7 Td²與I d²之比較…………………………………………………..…………………………50圖 七 r² = 0.9 Td²與I d²之比較……………………………………………………………………………..51圖 八 不同共線性下兩估計式之bias²…………………………………………………………………51圖 九 不同共線性下兩估計式之MSE…………………………………………………………………52圖 十 不同共線性下兩估計式之bias²與MSE…………………………………………………….52 zh_TW dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#B2002003827 en_US dc.subject (關鍵詞) 脊迴歸 zh_TW dc.subject (關鍵詞) 刀削法 zh_TW dc.subject (關鍵詞) 偏量估計式 zh_TW dc.subject (關鍵詞) Ridge Regression en_US dc.subject (關鍵詞) Jackknife en_US dc.subject (關鍵詞) Biased estimator en_US dc.title (題名) 改良式脊迴歸分析法於預測模式之應用 zh_TW dc.title (題名) Applied Improved Ridge Regression Analysis en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 1.林燦隆、謝邦昌、唐榮澤，(1989)，利用氣象因子建立甘蔗糖份含量之預測模式，台灣糖業研究所研究彙報，124:1-122.鄭敏祿，(1985)，脊廻歸估計之模擬研究。國立政治大學統計學研究所碩士論文。3.謝邦昌，(1991)，綜合預測模式之探討－甘蔗蔗產量及糖份含量依氣象因子二段式加權預測模式之研究。國立台灣大學農藝學研究所生物統計組博士論文。4. Brown, W.G. and Beattie, B.R. (1975).Improving Estimates Of Economic Parameters By Use Of Ridge Regression With Production Function Applications. Am.J.Agric.Econ.,57,21-325. Douglas, G.F.(1978).Ridge Regression:When Biased Estimation Is Better, Social Science Ouarterly, Vol.58,No.4,March: 708-7166. Draper, N. R. and Smith , H. (1981). Applied Regression Analysis, Second Edition, New York. 7.Ellen ,B.R.(1991). Prediction Error and Its Estimation for Subset-Selected Models, Technometrics, Vol.33, No.4,November:459-4678.Hinkley, D.V. (1977). Jackknifing In Unbalanced Situations, Technometrics, Vol.19,No.3,August:285-2929.Hoerl, A.E. and Kennard, R.W. (1970). Ridge Regression : Biased Estimation For Nonorthogonal Problems, Technometrics, Vol.12, No.1, February:55-6710. Hoerl, A.E. and Kennard, R.W. (1970). Ridge Regression : Applications to Nonorthogonal Problems , Technometrics, Vol.12, No.1, February:69-8311. Hoerl, A.E. Kennard, R.W. and Baldwin,K.F.(1975) Ridge Regression: Some Simulations, Communications In Statistics, 4(2), 105-12312.Hoerl,A.E. and Kennard,R.W.(1976).Ridge Regression : Iterative Estimation Of The Biased Parameter, Commun.Statis. Theor. Meth.A5(1):77-8813.John Neter, (1989). Applied Linear Regression Models, Second Edition, Boston.14.Loesgen,K.H.(1990). Generalization and Bayesian Interpretation of Ridge-Type Estimators with Good Prior Means, Statistical Papers, 31:147-15715.McDonald ,G.C. and Galarneau,D.I. (1975). A Monte Carlo evaluation of Some Ridge Type estimators.JASA,70:407-41616.Miller,R.G. (1968) Jackkinfing Variance. Ann.Math.Stqtist.,39:567-58217.Miller,R.G. (1974). An Unbalanced Jackknife, The Annals Of Statistics, Vol 2, No.5:880-89118.Nityananda Sarkar, (1992), A New Estimator Combining The Ridge Regression And The Restricted Least Squares Methods Of Estimation, Commun. Statist. Theory Meth.,21(7):1987-200019.Nordberg, L. (1982). A Procedure For Determination Of A Good Ridge Parameter In Linear Regression. Commun. Statist. B11:285-30920.Quenouille,M.H.(1956).Note On Bias In Estimation. Biometrika. 43:353-36021.SAS/IML User’s Guide.(1985). SAS Institute Inc. North Carolina.22.Segerstedt,B.(1992).On Ordinary Ridge Regression In Generalized Linear Models, Commun.Statist.-Theory Meth., 21(8):2227-224623.Shao,J. and Wu,C.F.J. (1987), Heterpscedastocoty-Robustness Of Jackknife Variance Estimators In Linear Models, The Annals Of Statistics, Vol.15 ,No. 4:1563-157924.Shao,J.(1992).Jackknifing In Generalized Linear Models, Ann.Inst. Statist. Math. Vol.44,No. 4,673-68625. Turkey, J.W. (1958) Bias And Confidence In Not-Quite Large Samples. Ann.Math.Statist.,29:614 zh_TW
