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題名 離散判別分析之變數選取法研究
離散判別分析之變數選取法研究
作者 陳燕鑾
貢獻者 黃登源
陳燕鑾
日期 1988
上傳時間 4-五月-2016 14:24:57 (UTC+8)
參考文獻 參考文獻
     1. Anderson, J. A. [1972]: “Separate sample logistic discrimination.” Biometrika, 59, 19-36.
     2. Anderson, T. W. [1952]: An Introduction to Multivariate Statistical Methods, New York: Wiley.
     3. Bahadur, R. R. [1961]: “A representation of the joint distribution of response to n dichotomous items.” In Studies in Item Analysis and Prediction, H. Solomon (Ed.), Palo Alto, Calif.: Stanford Univ. Press, pp. 158-168..
     4. Dillon, W. R. and M. Goldstein, [1978]: “On the performance of some multinomial classification rules,” J. Am. Stat. Assoc., 78, no. 362.
     5. Gilbert, E. S. [1968]: “On discrimination using qualitative variables,” J. Am. Stat. Assoc., 63, 1399.
     6. Glick, N. [1972]: “Sample – based classification procedures derived from density estimators,” J. Am. Stat. Assoc., 67, 166-122.
     7. Glick, N. [1973]: “Sample – based mutinomial classification,” Biometrics, 29, 241-256.
     8. Goldstein, M. [1975]: “Comparison of some density estimate classification procedures,” J. Am. Stat. Assoc., 70, 666-669.
     9. Goldstein, M. and W. R. Dillon, [1977]: “A stepwise discrete variable selection procedure,” Commun. Stat., Theory and Material, 6, 1423-36.
     10. Glodstein, M. and W. R. Dillon, [1978]: Discrete Discriminant Analysis, John Wiley & Sons, Inc., New York.
     11. Goldstein, M. and M. Rabinowitz, [1975]: “Selection of variates for the two-group multinomial classification problem,” J. Am. Stat. Assoc., 70, 776-781.
     12. Haberman, S. J. [1974]: The analysis of frequency data, The University of Chicago Press, Ltd., London.
     13. Hoel, P. G. and R. P. Peterson [1949]: “A solution to the problem of optimum classification,” Ann. Math. Stat., 20, 433-438.
     14. Hills, M. [1967]: “Discrimination and allocation with discrete data,” J. Roy. Stat. Soc., C16, 237-250.
     15. Johnson, R. A. and Wichern, D. W. [1986]: Applied Multivariate Statistical Analysis, Prentice- Hall, Inc., Englewood Cliffs, New Jersey.
     16. Kennedy, Jr. W. J. and Gentle, J. E. [1980]: Statistical Computing, 華泰書局, pp192-200.
     17. Kullback, S. [1959]: Information Theory and Statistics, New York: Wiley.
     18. Lanchin, P. A. [1975]: Discriminant Analysis, Hafner Press, New York.
     19. Lachin, J. M. [1973]: “On a stepwise procedure for two populations Bayes decision rules using discrete variables,” Biometrics, 29, 551-564.
     20. Martin, D. C. and R. A. Bradley, [1972]: “Probability models estimation and classification for multivariate dichotomous populations,” Biometrics, 28, 203-222.
     21. Matusita, K. [1955]: “Decision rules based on the distance for problems of fit, two samples and estimation,” Ann. Math. Stat. 26, 631-640.
     22. Moore, D. H., II [1973]: “Evaluation of five discrimination procedures for binary variables,” J. Am. Stat. Assoc., 68-339-404.
     23. SAS USER’S GUIDE: Statistics [1982], SAS INSTITUTE INC. CARY, NORTH CAROLINA.
     24. Solomon, H. (Ed.) [1961]: Studies in Item Analysis & Prediction, Palo Alto, Calif.: Stanford University Press.
     25. Weiner, J. and O. J. Dunn, [1966]: “Elimination of variates in linear discrimination problem,” Biometrics, 22, 268.
     26. Welch, B. L. [1939]: “Note on discriminant functions,” Biometrika, 31, 218-220.
參考文獻
     1. Anderson, J. A. [1972]: “Separate sample logistic discrimination.” Biometrika, 59, 19-36.
     2. Anderson, T. W. [1952]: An Introduction to Multivariate Statistical Methods, New York: Wiley.
     3. Bahadur, R. R. [1961]: “A representation of the joint distribution of response to n dichotomous items.” In Studies in Item Analysis and Prediction, H. Solomon (Ed.), Palo Alto, Calif.: Stanford Univ. Press, pp. 158-168..
     4. Dillon, W. R. and M. Goldstein, [1978]: “On the performance of some multinomial classification rules,” J. Am. Stat. Assoc., 78, no. 362.
     5. Gilbert, E. S. [1968]: “On discrimination using qualitative variables,” J. Am. Stat. Assoc., 63, 1399.
     6. Glick, N. [1972]: “Sample – based classification procedures derived from density estimators,” J. Am. Stat. Assoc., 67, 166-122.
     7. Glick, N. [1973]: “Sample – based mutinomial classification,” Biometrics, 29, 241-256.
     8. Goldstein, M. [1975]: “Comparison of some density estimate classification procedures,” J. Am. Stat. Assoc., 70, 666-669.
     9. Goldstein, M. and W. R. Dillon, [1977]: “A stepwise discrete variable selection procedure,” Commun. Stat., Theory and Material, 6, 1423-36.
     10. Glodstein, M. and W. R. Dillon, [1978]: Discrete Discriminant Analysis, John Wiley & Sons, Inc., New York.
     11. Goldstein, M. and M. Rabinowitz, [1975]: “Selection of variates for the two-group multinomial classification problem,” J. Am. Stat. Assoc., 70, 776-781.
     12. Haberman, S. J. [1974]: The analysis of frequency data, The University of Chicago Press, Ltd., London.
     13. Hoel, P. G. and R. P. Peterson [1949]: “A solution to the problem of optimum classification,” Ann. Math. Stat., 20, 433-438.
     14. Hills, M. [1967]: “Discrimination and allocation with discrete data,” J. Roy. Stat. Soc., C16, 237-250.
     15. Johnson, R. A. and Wichern, D. W. [1986]: Applied Multivariate Statistical Analysis, Prentice- Hall, Inc., Englewood Cliffs, New Jersey.
     16. Kennedy, Jr. W. J. and Gentle, J. E. [1980]: Statistical Computing, 華泰書局, pp192-200.
     17. Kullback, S. [1959]: Information Theory and Statistics, New York: Wiley.
     18. Lanchin, P. A. [1975]: Discriminant Analysis, Hafner Press, New York.
     19. Lachin, J. M. [1973]: “On a stepwise procedure for two populations Bayes decision rules using discrete variables,” Biometrics, 29, 551-564.
     20. Martin, D. C. and R. A. Bradley, [1972]: “Probability models estimation and classification for multivariate dichotomous populations,” Biometrics, 28, 203-222.
     21. Matusita, K. [1955]: “Decision rules based on the distance for problems of fit, two samples and estimation,” Ann. Math. Stat. 26, 631-640.
     22. Moore, D. H., II [1973]: “Evaluation of five discrimination procedures for binary variables,” J. Am. Stat. Assoc., 68-339-404.
     23. SAS USER’S GUIDE: Statistics [1982], SAS INSTITUTE INC. CARY, NORTH CAROLINA.
     24. Solomon, H. (Ed.) [1961]: Studies in Item Analysis & Prediction, Palo Alto, Calif.: Stanford University Press.
     25. Weiner, J. and O. J. Dunn, [1966]: “Elimination of variates in linear discrimination problem,” Biometrics, 22, 268.
     26. Welch, B. L. [1939]: “Note on discriminant functions,” Biometrika, 31, 218-220.
描述 碩士
國立政治大學
統計學系
資料來源 http://thesis.lib.nccu.edu.tw/record/#B2002005741
http://thesis.lib.nccu.edu.tw/record/#B2002005741
資料類型 thesis
thesis
dc.contributor.advisor 黃登源zh_TW
dc.contributor.author (作者) 陳燕鑾zh_TW
dc.creator (作者) 陳燕鑾zh_TW
dc.date (日期) 1988en_US
dc.date.accessioned 4-五月-2016 14:24:57 (UTC+8)-
dc.date.available 4-五月-2016 14:24:57 (UTC+8)-
dc.date.issued (上傳時間) 4-五月-2016 14:24:57 (UTC+8)-
dc.identifier (其他 識別碼) B2002005741en_US
dc.identifier (其他 識別碼) B2002005741en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/90507-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/90507-
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 目錄
     第一章 緒論………1
     第一節 研究動機與目的………1
     第二節 本文結構………1
     第二章 離散判別分析的基本理論………3
     第一節 緒言………3
     第二節 離散判別分析的基本觀點………4
     第三節 完全多項式模型下的樣本法………6
     第三章 以判別值距離d為基礎之變數選取………10
     第一節 理論基礎………10
     第二節 以判別值距離d為基礎之變數選取法………13
     第三節 舉例………16
     第四章 計算方法………27
     第五章 模擬分析………31
     第六章 結論………34
     附錄一………35
     附錄二………40
     附錄三………43
     參考文獻………44		zh_TW
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#B2002005741en_US
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#B2002005741en_US
dc.title (題名) 離散判別分析之變數選取法研究zh_TW
dc.title (題名) 離散判別分析之變數選取法研究zh_TW
dc.type (資料類型) thesisen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) 參考文獻
     1. Anderson, J. A. [1972]: “Separate sample logistic discrimination.” Biometrika, 59, 19-36.
     2. Anderson, T. W. [1952]: An Introduction to Multivariate Statistical Methods, New York: Wiley.
     3. Bahadur, R. R. [1961]: “A representation of the joint distribution of response to n dichotomous items.” In Studies in Item Analysis and Prediction, H. Solomon (Ed.), Palo Alto, Calif.: Stanford Univ. Press, pp. 158-168..
     4. Dillon, W. R. and M. Goldstein, [1978]: “On the performance of some multinomial classification rules,” J. Am. Stat. Assoc., 78, no. 362.
     5. Gilbert, E. S. [1968]: “On discrimination using qualitative variables,” J. Am. Stat. Assoc., 63, 1399.
     6. Glick, N. [1972]: “Sample – based classification procedures derived from density estimators,” J. Am. Stat. Assoc., 67, 166-122.
     7. Glick, N. [1973]: “Sample – based mutinomial classification,” Biometrics, 29, 241-256.
     8. Goldstein, M. [1975]: “Comparison of some density estimate classification procedures,” J. Am. Stat. Assoc., 70, 666-669.
     9. Goldstein, M. and W. R. Dillon, [1977]: “A stepwise discrete variable selection procedure,” Commun. Stat., Theory and Material, 6, 1423-36.
     10. Glodstein, M. and W. R. Dillon, [1978]: Discrete Discriminant Analysis, John Wiley & Sons, Inc., New York.
     11. Goldstein, M. and M. Rabinowitz, [1975]: “Selection of variates for the two-group multinomial classification problem,” J. Am. Stat. Assoc., 70, 776-781.
     12. Haberman, S. J. [1974]: The analysis of frequency data, The University of Chicago Press, Ltd., London.
     13. Hoel, P. G. and R. P. Peterson [1949]: “A solution to the problem of optimum classification,” Ann. Math. Stat., 20, 433-438.
     14. Hills, M. [1967]: “Discrimination and allocation with discrete data,” J. Roy. Stat. Soc., C16, 237-250.
     15. Johnson, R. A. and Wichern, D. W. [1986]: Applied Multivariate Statistical Analysis, Prentice- Hall, Inc., Englewood Cliffs, New Jersey.
     16. Kennedy, Jr. W. J. and Gentle, J. E. [1980]: Statistical Computing, 華泰書局, pp192-200.
     17. Kullback, S. [1959]: Information Theory and Statistics, New York: Wiley.
     18. Lanchin, P. A. [1975]: Discriminant Analysis, Hafner Press, New York.
     19. Lachin, J. M. [1973]: “On a stepwise procedure for two populations Bayes decision rules using discrete variables,” Biometrics, 29, 551-564.
     20. Martin, D. C. and R. A. Bradley, [1972]: “Probability models estimation and classification for multivariate dichotomous populations,” Biometrics, 28, 203-222.
     21. Matusita, K. [1955]: “Decision rules based on the distance for problems of fit, two samples and estimation,” Ann. Math. Stat. 26, 631-640.
     22. Moore, D. H., II [1973]: “Evaluation of five discrimination procedures for binary variables,” J. Am. Stat. Assoc., 68-339-404.
     23. SAS USER’S GUIDE: Statistics [1982], SAS INSTITUTE INC. CARY, NORTH CAROLINA.
     24. Solomon, H. (Ed.) [1961]: Studies in Item Analysis & Prediction, Palo Alto, Calif.: Stanford University Press.
     25. Weiner, J. and O. J. Dunn, [1966]: “Elimination of variates in linear discrimination problem,” Biometrics, 22, 268.
     26. Welch, B. L. [1939]: “Note on discriminant functions,” Biometrika, 31, 218-220.		zh_TW
dc.relation.reference (參考文獻) 參考文獻
     1. Anderson, J. A. [1972]: “Separate sample logistic discrimination.” Biometrika, 59, 19-36.
     2. Anderson, T. W. [1952]: An Introduction to Multivariate Statistical Methods, New York: Wiley.
     3. Bahadur, R. R. [1961]: “A representation of the joint distribution of response to n dichotomous items.” In Studies in Item Analysis and Prediction, H. Solomon (Ed.), Palo Alto, Calif.: Stanford Univ. Press, pp. 158-168..
     4. Dillon, W. R. and M. Goldstein, [1978]: “On the performance of some multinomial classification rules,” J. Am. Stat. Assoc., 78, no. 362.
     5. Gilbert, E. S. [1968]: “On discrimination using qualitative variables,” J. Am. Stat. Assoc., 63, 1399.
     6. Glick, N. [1972]: “Sample – based classification procedures derived from density estimators,” J. Am. Stat. Assoc., 67, 166-122.
     7. Glick, N. [1973]: “Sample – based mutinomial classification,” Biometrics, 29, 241-256.
     8. Goldstein, M. [1975]: “Comparison of some density estimate classification procedures,” J. Am. Stat. Assoc., 70, 666-669.
     9. Goldstein, M. and W. R. Dillon, [1977]: “A stepwise discrete variable selection procedure,” Commun. Stat., Theory and Material, 6, 1423-36.
     10. Glodstein, M. and W. R. Dillon, [1978]: Discrete Discriminant Analysis, John Wiley & Sons, Inc., New York.
     11. Goldstein, M. and M. Rabinowitz, [1975]: “Selection of variates for the two-group multinomial classification problem,” J. Am. Stat. Assoc., 70, 776-781.
     12. Haberman, S. J. [1974]: The analysis of frequency data, The University of Chicago Press, Ltd., London.
     13. Hoel, P. G. and R. P. Peterson [1949]: “A solution to the problem of optimum classification,” Ann. Math. Stat., 20, 433-438.
     14. Hills, M. [1967]: “Discrimination and allocation with discrete data,” J. Roy. Stat. Soc., C16, 237-250.
     15. Johnson, R. A. and Wichern, D. W. [1986]: Applied Multivariate Statistical Analysis, Prentice- Hall, Inc., Englewood Cliffs, New Jersey.
     16. Kennedy, Jr. W. J. and Gentle, J. E. [1980]: Statistical Computing, 華泰書局, pp192-200.
     17. Kullback, S. [1959]: Information Theory and Statistics, New York: Wiley.
     18. Lanchin, P. A. [1975]: Discriminant Analysis, Hafner Press, New York.
     19. Lachin, J. M. [1973]: “On a stepwise procedure for two populations Bayes decision rules using discrete variables,” Biometrics, 29, 551-564.
     20. Martin, D. C. and R. A. Bradley, [1972]: “Probability models estimation and classification for multivariate dichotomous populations,” Biometrics, 28, 203-222.
     21. Matusita, K. [1955]: “Decision rules based on the distance for problems of fit, two samples and estimation,” Ann. Math. Stat. 26, 631-640.
     22. Moore, D. H., II [1973]: “Evaluation of five discrimination procedures for binary variables,” J. Am. Stat. Assoc., 68-339-404.
     23. SAS USER’S GUIDE: Statistics [1982], SAS INSTITUTE INC. CARY, NORTH CAROLINA.
     24. Solomon, H. (Ed.) [1961]: Studies in Item Analysis & Prediction, Palo Alto, Calif.: Stanford University Press.
     25. Weiner, J. and O. J. Dunn, [1966]: “Elimination of variates in linear discrimination problem,” Biometrics, 22, 268.
     26. Welch, B. L. [1939]: “Note on discriminant functions,” Biometrika, 31, 218-220.		zh_TW