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    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/20606

    Title: A note on determining the number of outliers in an exponential sample by least squares procedure
    Authors: Wu, Jong-wuu
    Contributors: 淡江大學統計學系
    Keywords: Least squares procedure;Upper outlier;Exponential distribution;Mean squared error;Order statistic;Pareto distribution
    Date: 2001-10
    Issue Date: 2009-11-30 12:53:31 (UTC+8)
    Publisher: Springer
    Abstract: In this paper, we suggest a least squares procedure for the determination of the number of upper outliers in an exponential sample by minimizing sample mean squared error. Moreover, the method can reduce the masking or “swamping” effects. In addition, we have also found that the least squares procedure is easy and simple to compute than test procedure Tk, suggested by Zhang (1998) for determining the number of upper outliers, since Zhang (1998) need to use the complicated null distribution of Tk. Moreover, we give three practical examples and a simulated example to illustrate the procedures. Further, simulation studies are given to show the advantages of the proposed method. Finally, the proposed least squares procedure can also determine the number of upper outliers in other continuous univariate distributions (for example, Pareto, Gumbel, Weibull, etc.).
    Relation: Statistical Papers 42(4), pp.489-503
    DOI: 10.1007/s003620100075
    Appears in Collections:[Graduate Institute & Department of Statistics] Journal Article

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