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Title貝氏多項式迴歸模型選取之研究
Creator洪幸如
HONG, XING-RU
Contributor鄭天澤
ZHENG, TIAN-ZE
洪幸如
HONG, XING-RU
Key Words多項式迴歸
貝氏選模法
Date1992
1991
Date Issued2-May-2016 15:17:40 (UTC+8)
參考文獻 Allen, D.M. (l971a), " Mean Square Error of Prediction as a Criterion for Selecting Variables" (with discussion), Technometrics, 13,469-481.
     Berger,J. (1988), Comment on 1/ Bayesian Variable Selection in Linear Regression", Journal of the American Statistical Association,83,1033-1034.
     Box, G.E.P. and Tiao, G.C.(l973), Bayesian Inference in Statistical Analysis, Reading,MA: Addison-Wesley.
     Draper, N.R. and Smith, H. (1981), Applied Regression Analysis. 2nd ed New York: Wiley.
     Guttman, I.(1967), "The Use of the Concept of a Future Observation in Goodness-of-Fit Problems", Journal of the Royal Statistical Society, Ser.B, 29, 83-100.
     Halpern, E.F.(l973), "Polynomial Regression From a Bayesian Approach", Journal of the American Statistical Association, 68, 137·143.
     Hocking, R.R.(l976), "The Analysis and Selection of Variables in Linear Regression", Biometrics, 32, 1-51.
     Kendall, M. and Stuart, A.(1977), The Advanced Theory of Statistics. Vol.1, 4th ed., London: Griffin.
     Kleinbaum / Kupper (1978), Applied Regression Analysis ,Duxbury Press.
     Linhart, H. and Zucchini, W.(1986), Model Selection. New York: Wiley.
     Mallows, C.L.(1973), "Some Comments on C ", Technometrics, 15, 661-675.
     Mitchell, T.J. and Beauchamp, J.J.(1986a), "Bayesian Variable Selection in Regression", Report ORNL-6328, Oak Ridge National Laboratory, Oak Ridge, TN.
     (1988), "Bayesian Variable Selection in Linear Regression"(with discussion), Journal of the American Statistical Association,83,1023-1036.
     Rainville, E.D.(1960), Special Functions. New York: Chelsea.
     San Martini, A. and Spezzaferri, P.(1984), "A Predictive Model Selection Criterion",Journal of the Royal Statistical Society,Ser.B, 46,296-303.
     Sansone, G.(1977), Orthogonal Functions. New York: Krieger.
     Smith, A.P.M. and Spiegelhalter, D.J.(1980), "Bayes Factors and Choice Criteria for Linear Models", Journal of the Royal Statistical Society, Ser.B, 42, 213-220.
     Spiegelhalter, DJ. and Smith, A.F.M.(1982), "Bayes Factors for Linear and Log-Linear Models with Vague Prior Information", Journal of the Royal Statistical Society, Ser.B, 44, 377-387.
     Thompson, M.L.(1978), "Selection of Variables in Multiple Regression ", International Statistical Review, 46, 1-49 and 129-146.
Description碩士
國立政治大學
統計學系
資料來源 http://thesis.lib.nccu.edu.tw/record/#B2002004657
Typethesis
dc.contributor.advisor 鄭天澤zh_TW
dc.contributor.advisor ZHENG, TIAN-ZEen_US
dc.contributor.author (Authors) 洪幸如zh_TW
dc.contributor.author (Authors) HONG, XING-RUen_US
dc.creator (作者) 洪幸如zh_TW
dc.creator (作者) HONG, XING-RUen_US
dc.date (日期) 1992en_US
dc.date (日期) 1991en_US
dc.date.accessioned 2-May-2016 15:17:40 (UTC+8)-
dc.date.available 2-May-2016 15:17:40 (UTC+8)-
dc.date.issued (上傳時間) 2-May-2016 15:17:40 (UTC+8)-
dc.identifier (Other Identifiers) B2002004657en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/89246-
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.tableofcontents 第一章緒論..........1
     第二章多項式迴歸的貝氏選模..........5
     2.1 正交多項式及其性質..........5
     2.2 貝氏選模法..........9
     2.2.1 符號說明及假設..........10
     2.2.2 事前分配..........10
     2.2.3 事後機率..........12
     2.2.4 γ的選擇..........15
     2.3 與Cp 的比較..........17
     第三章模擬結果分析..........19
     3.1 自變數服從常態分配..........19
     3.2 自變數服從均等分配..........22
     3.3 自變數服從加瑪分配..........24
     3.4 實例..........25
     第四章討論及建議..........27
     
     參考文獻..........38
zh_TW
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#B2002004657en_US
dc.subject (關鍵詞) 多項式迴歸zh_TW
dc.subject (關鍵詞) 貝氏選模法zh_TW
dc.title (題名) 貝氏多項式迴歸模型選取之研究zh_TW
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) Allen, D.M. (l971a), " Mean Square Error of Prediction as a Criterion for Selecting Variables" (with discussion), Technometrics, 13,469-481.
     Berger,J. (1988), Comment on 1/ Bayesian Variable Selection in Linear Regression", Journal of the American Statistical Association,83,1033-1034.
     Box, G.E.P. and Tiao, G.C.(l973), Bayesian Inference in Statistical Analysis, Reading,MA: Addison-Wesley.
     Draper, N.R. and Smith, H. (1981), Applied Regression Analysis. 2nd ed New York: Wiley.
     Guttman, I.(1967), "The Use of the Concept of a Future Observation in Goodness-of-Fit Problems", Journal of the Royal Statistical Society, Ser.B, 29, 83-100.
     Halpern, E.F.(l973), "Polynomial Regression From a Bayesian Approach", Journal of the American Statistical Association, 68, 137·143.
     Hocking, R.R.(l976), "The Analysis and Selection of Variables in Linear Regression", Biometrics, 32, 1-51.
     Kendall, M. and Stuart, A.(1977), The Advanced Theory of Statistics. Vol.1, 4th ed., London: Griffin.
     Kleinbaum / Kupper (1978), Applied Regression Analysis ,Duxbury Press.
     Linhart, H. and Zucchini, W.(1986), Model Selection. New York: Wiley.
     Mallows, C.L.(1973), "Some Comments on C ", Technometrics, 15, 661-675.
     Mitchell, T.J. and Beauchamp, J.J.(1986a), "Bayesian Variable Selection in Regression", Report ORNL-6328, Oak Ridge National Laboratory, Oak Ridge, TN.
     (1988), "Bayesian Variable Selection in Linear Regression"(with discussion), Journal of the American Statistical Association,83,1023-1036.
     Rainville, E.D.(1960), Special Functions. New York: Chelsea.
     San Martini, A. and Spezzaferri, P.(1984), "A Predictive Model Selection Criterion",Journal of the Royal Statistical Society,Ser.B, 46,296-303.
     Sansone, G.(1977), Orthogonal Functions. New York: Krieger.
     Smith, A.P.M. and Spiegelhalter, D.J.(1980), "Bayes Factors and Choice Criteria for Linear Models", Journal of the Royal Statistical Society, Ser.B, 42, 213-220.
     Spiegelhalter, DJ. and Smith, A.F.M.(1982), "Bayes Factors for Linear and Log-Linear Models with Vague Prior Information", Journal of the Royal Statistical Society, Ser.B, 44, 377-387.
     Thompson, M.L.(1978), "Selection of Variables in Multiple Regression ", International Statistical Review, 46, 1-49 and 129-146.
zh_TW