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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
Authors:	周玫芳 Chou, Mei Fang
Contributors:	謝邦昌 Shia, Ben Chang 周玫芳 Chou, Mei Fang
Keywords:	脊迴歸刀削法偏量估計式 Ridge Regression Jackknife Biased estimator
Date:	1994 1993
Issue Date:	2016-04-29 15:31:04 (UTC+8)
Abstract:	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
Reference:	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
Source URI:	http://thesis.lib.nccu.edu.tw/record/#B2002003827
Data Type:	thesis
Appears in Collections:	[Department of Statistics] Theses

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