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| Title | 改良式脊迴歸分析法於預測模式之應用 Applied Improved Ridge Regression Analysis |
| Creator | 周玫芳 Chou, Mei Fang |
| Contributor | 謝邦昌 Shia, Ben Chang 周玫芳 Chou, Mei Fang |
| Key Words | 脊迴歸 刀削法 偏量估計式 Ridge Regression Jackknife Biased estimator |
| Date | 1994 1993 |
| Date Issued | 29-Apr-2016 15:31:04 (UTC+8) |
| Summary | 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， 124:1-12 2.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.,57,21-32 5. Douglas, G.F.(1978).Ridge Regression:When Biased Estimation Is Better, Social Science Ouarterly, Vol.58,No.4,March: 708-716 6. 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:459-467 8.Hinkley, D.V. (1977). Jackknifing In Unbalanced Situations, Technometrics, Vol.19,No.3,August:285-292 9.Hoerl, A.E. and Kennard, R.W. (1970). Ridge Regression : Biased Estimation For Nonorthogonal Problems, Technometrics, Vol.12, No.1, February:55-67 10. Hoerl, A.E. and Kennard, R.W. (1970). Ridge Regression : Applications to Nonorthogonal Problems , Technometrics, Vol.12, No.1, February:69-83 11. Hoerl, A.E. Kennard, R.W. and Baldwin,K.F.(1975) Ridge Regression: Some Simulations, Communications In Statistics, 4(2), 105-123 12.Hoerl,A.E. and Kennard,R.W.(1976).Ridge Regression : Iterative Estimation Of The Biased Parameter, Commun.Statis. Theor. Meth.A5(1):77-88 13.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, 31:147-157 15.McDonald ,G.C. and Galarneau,D.I. (1975). A Monte Carlo evaluation of Some Ridge Type estimators.JASA,70:407-416 16.Miller,R.G. (1968) Jackkinfing Variance. Ann.Math.Stqtist.,39:567-582 17.Miller,R.G. (1974). An Unbalanced Jackknife, The Annals Of Statistics, Vol 2, No.5:880-891 18.Nityananda Sarkar, (1992), A New Estimator Combining The Ridge Regression And The Restricted Least Squares Methods Of Estimation, Commun. Statist. Theory Meth.,21(7):1987-2000 19.Nordberg, L. (1982). A Procedure For Determination Of A Good Ridge Parameter In Linear Regression. Commun. Statist. B11:285-309 20.Quenouille,M.H.(1956).Note On Bias In Estimation. Biometrika. 43:353-360 21.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):2227-2246 23.Shao,J. and Wu,C.F.J. (1987), Heterpscedastocoty-Robustness Of Jackknife Variance Estimators In Linear Models, The Annals Of Statistics, Vol.15 ,No. 4:1563-1579 24.Shao,J.(1992).Jackknifing In Generalized Linear Models, Ann.Inst. Statist. Math. Vol.44,No. 4,673-686 25. Turkey, J.W. (1958) Bias And Confidence In Not-Quite Large Samples. Ann.Math.Statist.,29:614 |
| Description | 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 |
| Type | thesis |
| dc.contributor.advisor | 謝邦昌 | zh_TW |
| dc.contributor.advisor | Shia, Ben Chang | en_US |
| dc.contributor.author (Authors) | 周玫芳 | zh_TW |
| dc.contributor.author (Authors) | 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-Apr-2016 15:31:04 (UTC+8) | - |
| dc.date.available | 29-Apr-2016 15:31:04 (UTC+8) | - |
| dc.date.issued (上傳時間) | 29-Apr-2016 15:31:04 (UTC+8) | - |
| dc.identifier (Other Identifiers) | 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………………………………………………………………………………………………………….1 1-2 研究動機與目的……………………………………………………..……………………………………….2 1-3 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………………………………………………………………….…….………….9 2-2 Jackknife估計法之文獻探討…………………………………………………….……………….….11 2-3 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……………………………………………………………………………….…………………….14 3-2 Jackknife取一法………………………………………………..………………………………………….23 3-3 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…………………………………………………………………………….………………….……….34 4-2 電腦模擬………………………………………………………………………….…………………….……….38 4-3 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， 124:1-12 2.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.,57,21-32 5. Douglas, G.F.(1978).Ridge Regression:When Biased Estimation Is Better, Social Science Ouarterly, Vol.58,No.4,March: 708-716 6. 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:459-467 8.Hinkley, D.V. (1977). Jackknifing In Unbalanced Situations, Technometrics, Vol.19,No.3,August:285-292 9.Hoerl, A.E. and Kennard, R.W. (1970). Ridge Regression : Biased Estimation For Nonorthogonal Problems, Technometrics, Vol.12, No.1, February:55-67 10. Hoerl, A.E. and Kennard, R.W. (1970). Ridge Regression : Applications to Nonorthogonal Problems , Technometrics, Vol.12, No.1, February:69-83 11. Hoerl, A.E. Kennard, R.W. and Baldwin,K.F.(1975) Ridge Regression: Some Simulations, Communications In Statistics, 4(2), 105-123 12.Hoerl,A.E. and Kennard,R.W.(1976).Ridge Regression : Iterative Estimation Of The Biased Parameter, Commun.Statis. Theor. Meth.A5(1):77-88 13.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, 31:147-157 15.McDonald ,G.C. and Galarneau,D.I. (1975). A Monte Carlo evaluation of Some Ridge Type estimators.JASA,70:407-416 16.Miller,R.G. (1968) Jackkinfing Variance. Ann.Math.Stqtist.,39:567-582 17.Miller,R.G. (1974). An Unbalanced Jackknife, The Annals Of Statistics, Vol 2, No.5:880-891 18.Nityananda Sarkar, (1992), A New Estimator Combining The Ridge Regression And The Restricted Least Squares Methods Of Estimation, Commun. Statist. Theory Meth.,21(7):1987-2000 19.Nordberg, L. (1982). A Procedure For Determination Of A Good Ridge Parameter In Linear Regression. Commun. Statist. B11:285-309 20.Quenouille,M.H.(1956).Note On Bias In Estimation. Biometrika. 43:353-360 21.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):2227-2246 23.Shao,J. and Wu,C.F.J. (1987), Heterpscedastocoty-Robustness Of Jackknife Variance Estimators In Linear Models, The Annals Of Statistics, Vol.15 ,No. 4:1563-1579 24.Shao,J.(1992).Jackknifing In Generalized Linear Models, Ann.Inst. Statist. Math. Vol.44,No. 4,673-686 25. Turkey, J.W. (1958) Bias And Confidence In Not-Quite Large Samples. Ann.Math.Statist.,29:614 | zh_TW |