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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/41194

    Title: Nonparametric classification on two univariate distributions
    Authors: 林千代;Lin, Chien-tai
    Contributors: 淡江大學數學學系
    Keywords: Conditional probabilities of correct classification;Kolmogorov distance
    Date: 2001-02-01
    Issue Date: 2010-01-28 06:54:01 (UTC+8)
    Publisher: Taylor & Francis
    Abstract: A classification rule based on the minimum Kolmogorov distance for classifying an individual into one of two univariate populations is proposed. Some almost sure convergence theorems are derived and then utilized to study the limiting distributions of the conditional probabilities of correct classification. It is shown that the asymptotic distributions of the conditional probabilities of correct classification are normal under some mild conditions.
    Relation: Communications in Statistics: Theory and Methods 30(2), pp.319-330
    DOI: 10.1081/STA-100002034
    Appears in Collections:[Graduate Institute & Department of Mathematics] Journal Article

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