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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/90491


    Title: 主成份分析在各種多元統計方法上的應用
    Authors: 胡忠琳
    Contributors: 葉小蓁
    胡忠琳
    Date: 1989
    Issue Date: 2016-05-04 14:23:56 (UTC+8)
    Reference: 參考文獻
    一 、中文部分
    1 沈伊藤:主成份分析與其他統計分析之比較研究，台北:國立政治大學統計研究所碩士論文，民國七十五年。
    2 林清山:多變量分析統計法，台北:台灣東華書局，民國七十三年。
    3 黃俊英:多變量分析，三版，台北:中華經濟企業研究所 華泰經銷，民國七十七年。
    4 楊浩二. .多變量統計方法，台北:華泰書局，民國七三年。
    5 楊浩二:多變量常態檢定及應用之研究，台北:華泰書局民國七十一年。
    6 閩建蜀，游漢民：市場研究：基本方法，台北：巨浪出版社，民國七十五年。

    二、英文部分
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    2 Anderson. T.W. (1963) : Asymptotic theory for principal component analysis . Annals of Mathematical Statistics. Vol 34, PP. 122-148.
    3 Anderson. T.W. (1984) : An Introduction to Multivariate Statistical Analysis. New York: John Wiley and Son.
    4 Bartlett. M. S. (950) : Tests of significance in factor analysis. Brit. J. Psychol. Statist. Section. Vol 3. PP. 77
    5 Bartlett, M.S. (1951) : discriminant analysis. Vol 22 . pp.107-111. An inverse matrix adjustment in Annals of Mathematical Statistics.
    6 Berenson. H.L. Levine. D.H. and Goldstein (983): Intermediate Statistical Methods and Application A Computer Package Approach. Prentice - Hall. Inc .,Englewood Chiffs.
    New Jersey. pp.458-462.
    7 Cattell .R.B. (978): The Scientific Use of Factor Analysis in Beharioral and Life Sciences. New York: Plenum Press pP.15-39.
    8 Chang. W.C. (979) : Confidence interval estimation and transformation of data in a mixture of two multivariate normal distributions with any given large dimension. Technometrics,
    Vol 21 . PP. 351-355.
    9 Chang. W.C. (1983) : On using principal components before separating a mixture of two multivariate normal distributions. Applied Statistics. Vol 32, pp.267-275.
    10 Cravens. D.W., Woodruff. R.B. and Stamper. J.C. (1972) : An analytical approach for evaluating sales territory performance. Journal of Marketing. pp.31-37.
    11 Daling. J.R. and Tamura. H. (1970) Use of orthogonal factors for selection of variables in a regression equation an illustration. Applied Statistics. Vol 19. pp.260-268.
    12 Day. ICE. (969): Estimating the components of a mixture of normal distributions. Biometrika. Vol 56, pp.463-474.
    13 Draper. N.R.. and Smith. H. (981) :Analysis. 2nd ed. New York: John pp. 294-325. Applied Regression Wiley and Son Inc .,pp.294-325
    14 Dunham. R.B. (1977): Reaction to job characteristics: moderating effects of the origanization. Academy of Management Journal. Vol 20 .no. 1 . pp.42-65.
    15 Eastment. H.T.. and Krzanowski. W.J. (1982) Cross-Validatory choice of the number of components from a principal component analysis. Technometrics, Vol 24 ,pp.73-77
    16 Everitt. B.S. (1980) : Cluster Analysis. 2nd ed London Heinemann Educational Books.
    17 Filliben, J.J. (1975) The probability plot correlation coefficient test for normality. Technometrics. Vol 17. no. 1,pp.1l1-117.
    18 Finn. J.D. (1974): A General Model for Multivariate Analysis. New York Holt Rinehart and Winston. pp.182-204.
    19 Gabriel, K.R. (1971): The biplot graphic display of matrices by additive and multiplicative models. Journal of Royal Statistical Society B. Vol 40 . pp.186-196.
    20 Gnanadesikan. R. and Kettenring. J.R. (1972) Robust es – timates, residuals. and outlier detection with wultiresponse data. Biometrics. vol 28. pp.81-124.
    21 Goodnight. J. and Wallace. T.D. (1972) : Operational techniques and tables for making weak MSE tests for restrications in regression. Econometrica. Vol 40 . pp.699-709.
    22 Gordon. A.D. (1981) Classification Method for the Exploratory Analysis of Multivariate Data. London : Chapman and Hall.
    23 Gower. J.C. (1966) : Some distance properties of latent root and vector methods used in multivariate analysis. Biometrika .Vol 53. pp.325-338 .
    24 Gunst. R. F. and Mason. R. L. (1980): Regress i on Analysis and Its Application: Data-Oriented Approach. New York: Dekker pp.327-328.
    25 Hartigan. J.A. (1975): Clustering Algorithms New York : Wiley.
    26 Hawkins ,D.M. (1974) : The dection of errors in multivariate data using principal components. Journal of the American Statistical Association. Vol 59, pp.340-344.
    27 Hawkins, D.M. and Fatti, L.P. (1984) : Exploring multivariate data using the minor principal components, Statistican, Vol 33, pp.325-338.
    28 Hill, R.C. , Fomby, T.B. and Johnson, S.R. (1977): Component selection norms for principal components analysis. Communications in Statistics. Vol A6 , pp.309-334.
    29 Hotelling. H. (1933) Analysis of a complex of statistical variables into principal component. Journal of Educational Psychology, Vol 24 , pp.417-441 , 498-520.
    30 Hsuan. F.C. (1981) Ridge regression from principal component point of view. Communication in Statistics. Vol A10, pp.1981-1995.
    31 Jeffers. J.K.R. (1955): Principal component analysis in taxonomic research. Statistician, Vol 15, pp.207-208.
    32 Jeffers, J.N.R. (1967) : Two case studies in the application of principal component analysis. Applied Statistics, Vol 16, pp.225-236.
    33 Johnson, R.A. and Wichern, D.W. (1982): Applied Multivariate Statistical Analysis. New Jersey: Prentice -Hall, Inc.
    34 Jolliffe, I.T. (1972) :Discarding variabies in a principal component analysis I: Applied Statistics,Vol 21 ,pp.160-173
    35 Jolliffe, I.T. (1973) : Discarding variables in a principal component analysis 1I : Real data. Applied Statistics, Vol 22. pp.21-31.
    36 Jolliffe, LT. (986) Principal Component Analysis, New York: Springer-Verlag New York Inc.
    37 Lachenbruch. P.A. (975) : Discriminant Analysis, New York Hafner Press.
    38 Lowley, D.N. and Maxwell. A.E. (1971) Factor Analysis as a Statistical Method. 2nd ed. London: Butterworth.
    39 Halkovich. J.F. and Afifi, A.A. (1973): One tests for Multivariate normality. Journal of the American Statistical Association. Vol 68. PP. 176-179.
    40 Mansfield. E.R ., Webster. J.T. and Gunst. R.F. (1977) An analytic variable selection technique for principal component regression. Appl ied Statistics. Vol 26. PP. 34-40.
    41 Mardia. K. V. (1970) Measure of multivariate skewness and kurtosis with application. Biometrika. Vol 57. Pp. 519-530.
    42 Mardia. K.V .,Kent. J.T. and Bibby. J.M. (1979) : Multivariate Analysis. New York: Academic Press. PP. 394-406.
    43 Mezzich. J.E. and Solomon. H. (1980) Taxonomy and Behavioral Science: Comparative Performance of Grouping Methods. New York: Academic Press. Pp. 35-41.
    44 Morrison. D.F. (1967) Multivariate Statistical Methods. New York: McGraw-Hill. pp. 259-264.
    45 Mosteller. F. and Tukey. J.W. (1977) Regression: A Second Course in Statistics.
    Addison-Wesley. pp. 397-398. Data Analysis and Reading, MA: Addison-Wesley,pp.397-398 46 Muller. K.E. (1982) Understanding canonical correlation through the general linear model and principal components. American Statistican. Vol 36. PP. 342-354.
    47 Pearson. K. (1901): On lines and planes of closest fit to systems of points in place. Phil. Mag. (6) ,Vol 2. PP. 559-
    48 Press. S.J. (1972): Applied Multivariate Analysis. New York : Holt. Rinehart and Winston. PP. 305-319.
    49 Punj. G. and Stewart. D.W. (1983): Cluster analysis in marketing rese arch: review and suggestions for application. Journal of Marketing Research. Vol 10. PP. 144-145.
    50 Rao. C.R. (1964) The use and interpretation of principal component analysis in applied research. Sankhya A. Vol 26. PP. 329-358.
    51 Rao, C.R. (1973) Linear Statistical Inference and Its Applications 2nd ed. New York: John Wiley, pp. 582-587.
    52 Tatsuoka, M.M. (1971) : Multivariate Analysis Techniques for Educational and Psychological Research, New York: John Wiley.
    53 Toro-Vizcarrondo, C. and Wallace, T.D. (1968): A test of the mean square error criterion for restrictions in linear regression, Journal of the American Statistical Association,
    Vol 63, PP. 558-572.
    54 Wallace, T.D. and Toro-Vizcarrondo, C. (1969) Tables for the mean squares error test for exact linear restrictions in regression, Jouranl of the American Statistical Association,
    Vol 64, PP. 1649-1663.
    55 Wolfe, J.H. (1970): Pattern clustering in multivariate mixture analysis, Multivariate Behaviour Research, Vol 5, PP. 329-350.
    56 Younger, M.S. (1979) : A First Course in Linear Regression. By Boston: Duxbury Press, PP. 479-481.
    Description: 碩士
    國立政治大學
    統計學系
    Source URI: http://thesis.lib.nccu.edu.tw/record/#B2002005725
    Data Type: thesis
    Appears in Collections:[Department of Statistics] Theses

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