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    政大機構典藏 > 商學院 > 統計學系 > 學位論文 >  Item 140.119/30926
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/30926


    Title: 混合連續與間斷資料之馬式距離的穩健估計
    Robust estimation of the Mahalanobis distance for multivariate data mixed with continuous and discrete variables
    Authors: 任嘉珩
    Jen , Chia Heng
    Contributors: 鄭宗記
    任嘉珩
    Jen , Chia Heng
    Keywords: 混合型資料
    隱藏常態變數模型
    穩健估計
    馬式距離
    mixed data
    normal latnet variable model
    robust estimation
    Mahalanobis distacne
    minimum covariance determinant
    Date: 2007
    Issue Date: 2009-09-14
    Abstract: 本研究採用Lee 和Poon 所提出的隱藏常態變數模型來估計混合連續與間斷型變數之參數估計,並估計其馬式距離。此外,並利用穩健估計來估計混合型資料參數及其馬式距離,可在有離群值時解決最大蓋似估計的不穩定。
    Poon and Lee (1987) applied normal latent variable model to deal with the parameters
    estimation for the data mixed with continuous and discrete variables and Bedrick et al. (2000) used this idea to evaluate the Mahalanobis distance. In this thesis, we extend a similar idea to robustly estimate Multivariate Data Mixed with Continuous and Discrete Variables with the same model. Furthermore, we evaluate the Mahalanobis distance which can determine similarity of variables. The proposed method can overcome the unreliability of MLE while there exist outliers in the data.
    Reference: [1] Barnett, V. and Lewis, T. (1994), Outliers in Statistical Data, 3rd ed. New York:
    John Wiley and Sons.
    [2] Bedrick, E. J., Lapidus, J., and Powell, J. F. (2000), Estimating the Mahalanobis
    Distance from Mixed Continuous and Discrete Data, Biometrics, 56, 394–401.
    [3] Bhattacharyya, A. (1943), On a measure of divergence between two statistical
    populations defined by their probability distributions, Bulletin of the Calcutta
    Mathematical Society, 35, 99–109.
    [4] Donoho, D. L., and Huber,P. J. (1983), The Notion of Breakdown Point. In A
    Festschrift for Erich L. Lehmann, Ed. P. J. Bickel, K. A. Docksum and J. L.
    Hodges, Jr., 157–84, Belmont CA: Wadsworth.
    [5] Hampel, F., Ronchetti, P., Rousseeuw, P., and Stahel, W. (1986), Robust Statistics:
    The Approach Based on Influence Functions, New York: John Wiley and
    Sons.
    [6] Huber, Peter. J. (1964), Robust estimation of a location parameter, The Annals
    of Mathematical Statistics, 35, 73–101.
    [7] Huber, Peter. J. (1981), Robust Statistics, New York: John Wiley and Sons.
    [8] Jobsin, J. D. (1992), Applied Multivariate Data Analysis: Volume II: Categorical
    and Multivariate Methods, New York: Springer-Verlag.
    [9] Krzanowski, W. J. (1975), Discrimination and classfication using both binary
    and continuous variables, Journal of the American Statistical Association, 70,
    782–790.
    [10] Krzanowski, W. J. (1983), Distance between population using mixed continuous
    and categorical variables, Biometrika, 70, 235–243.
    [11] Lehmann, E. L. and Casella, G. (1998), Theory of Point Estimation, New York:
    Springer.
    [12] Krzanowski, W. J. and Marriott, F. H. C. (1995), Kendall’s Library of Statistics
    2, Maltivariate Analysis Part 2, London: Arnold.
    [13] Mahalanobis, P. C. (1936), On the generalized distance in statistics, Proceedings
    of the National Institute of Science India, 2, 49–55.
    [14] Mardia, K. V., Kent, J. T. and Bibby, J. M. (1979), Multivariate Analysis,
    London: Academic Press.
    [15] Maronna, R. A., Martin, R. D. and Yohai, V. J. (2006), Robust Statistics, Theory
    and Methods, New York: Wiley.
    [16] Matusita, K. (1972), Discrimination and the affinity of distributions, Sidcriminant
    Analysis and Applications, Ed. T. Cacoullos, pp.213-223, New York: Academic
    Press.
    [17] Olkin,I. and Tate, R. F. (1961), Multivariate correlation models with mixed
    discrete and continuous variables, Annals of Mathematical Statistics, 32, 448–
    465.
    [18] Poon, W. Y. and Lee, S. Y. (1986), Maximum likelihood estimation of polyserial
    correlations, Psychometrika, 51, 113–121.
    [19] Poon, W. Y. and Lee, S. Y. (1987),Maximum likelihood estimation of multivariate
    polyserial and polychoric correlation coefficients, Psychometrika, 52, 409–
    430.
    [20] Prohorov, Y. V. (1956), Convergence of random processes and limit theorems in
    probability theory, Theory of Probability and its Applications, 1, 157–214.
    [21] Rousseeuw, P. J. (1984), Least median of squares regression, Journal of the
    American Statistical Association, 79, 871–880.
    [22] Rousseeuw, P. J. and A. M. Leroy (1987), Robust Regression and Outlier Detection,
    New York: John Wiley.
    [23] Rousseeuw, P. J. and Van Driessen, K. (1999), A fast algorithm for the minimum
    covariance determinant estimator. Technometrics, 41, 212V223.
    [24] Zaman, A., Rousseeuw, P. J., and Orhan, M. (2001), Econometric applications
    of high-breakdown robust regression techiniques, Econometrics Letters, 71, 1–8.
    Description: 碩士
    國立政治大學
    統計研究所
    95354024
    96
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0095354024
    Data Type: thesis
    Appears in Collections:[統計學系] 學位論文

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