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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/27378


    Title: Weighted quasi-likelihood estimation based on fuzzy clustering analysis method and dimension reduction technique
    Authors: 吳忠武;Wu, Jong-wuu;Tsai, Tzong-Ru
    Contributors: 淡江大學統計學系
    Keywords: Dimension reduction technique;Optimal fuzzy clustering method;Outlier;Ordinary least squares estimator;Monte Carlo simulation
    Date: 2002-06-16
    Issue Date: 2009-12-30 14:59:06 (UTC+8)
    Publisher: Elsevier
    Abstract: For simplifying the fuzzy-weighted quasi-likelihood estimation procedure and reducing the influence of outliers in quasi-likelihood estimation, optimal fuzzy clustering analysis method and dimension reduction technique are combined to develop a modified fuzzy-weighted quasi-likelihood estimation method. Under some weak conditions, the asymptotic properties of modified fuzzy-weighted quasi-likelihood estimator are derived. Simulation results show that the modified fuzzy-weighted quasi-likelihood estimator performs well in finite sample. Moreover, the method is studied on several examples.
    Relation: Fuzzy Sets and Systems 128(3), pp.353-364
    DOI: 10.1016/S0165-0114(01)00200-7
    Appears in Collections:[統計學系暨研究所] 期刊論文

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