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    政大機構典藏 > 商學院 > 統計學系 > 期刊論文 >  Item 140.119/62351
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/62351

    Title: Identifying the distribution difference between two populations of fuzzy data based on a nonparametric statistical method
    Authors: 吳柏林
    Contributors: 應數系
    Date: 2013-11
    Issue Date: 2013-12-10 17:14:43 (UTC+8)
    Abstract: Nonparametric statistical tests are a distribution-free method without any assumption that data are drawn from a particular probability distribution. In this paper, to identify the distribution difference between two populations of fuzzy data, we derive a function that can describe continuous fuzzy data. In particular, the Kolmogorov–Smirnov two-sample test is used for distinguishing two populations of fuzzy data. Empirical studies illustrate that the Kolmogorov–Smirnov two-sample test enables us to judge whether two independent samples of continuous fuzzy data are derived from the same population. The results show that the proposed function is successful in distinguishing two populations of continuous fuzzy data and useful in various applications.
    Relation: IEEJ Transactions on Electronics, Information and Systems,8(6),591-598
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1002/tee.21901
    DOI: 10.1002/tee.21901
    Appears in Collections:[統計學系] 期刊論文

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