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    政大機構典藏 > 商學院 > 統計學系 > 學位論文 >  Item 140.119/60437
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/60437


    Title: 以無母數方法來檢測變異
    A nonparametric test for detecting increasing variability
    Authors: 鄭雅文
    Cheng, Ya Wen
    Contributors: 黃子銘
    Huang, Tzee Ming
    鄭雅文
    Cheng, Ya Wen
    Keywords: 無母數檢定
    變異
    nonparametric test
    variability
    Date: 2010
    Issue Date: 2013-09-05 15:11:55 (UTC+8)
    Abstract: 當我們探討的是兩組樣本的變異是否有所差異時,常見的方法有以ANOVA 為
    基礎的檢定與秩檢定,傳統的秩檢定需要假設兩母體具有相同的中位數或知道
    其差異。本研究採用Moses (1963) 提出的rank-like 檢定方法,此方法在處理兩組樣本的變異問題時,優點是不需要估計任何中心參數,也不需要假設母體中心參數相同,在資料偏態的情況下也表現得很穩健,我們試圖在樣本數極小的情況下對此方法作修正,將此檢定方法與以ANOVA 為基礎的檢定和秩檢定進行模擬比較,以能夠良好的控制型一誤差與檢定力作為評斷標準。由模擬的結果可得知,rank-like 檢定方法與修正後的方法在不同的分配下皆表現的穩健而修正後的方法特別適用於小樣本的情形。
    We consider the problem of detecting variability change in the two-sample case.Several classical variability tests are investigated, including the ANOVA based tests and the rank tests. Traditional two-sample rank tests assume that the location parameters for both samples are identical or of known difference. In this thesis, a modified version of the distribution-free rank-like test proposed by Moses (1963) is proposed. Moses’s test has several advantages. It does not require location parameter estimation, is applicable without assuming that location parameter are identical, and is robust for skewed data. However, Moses’s test has no power when each of the two samples has size 5 or less. The modified version of Moses’s test proposed in this thesis has some power when the sample sizes are small. Comparative
    simulation results are presented. According to these results, both Moses’s test and the proposed test are robust under all conditions, and the proposed test
    works better when the sample sizes are small.
    Reference: [1] 洪志真. 監控製程變異之SPC 方法(II). 2003.
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    Description: 碩士
    國立政治大學
    統計研究所
    98354001
    99
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0098354001
    Data Type: thesis
    Appears in Collections:[統計學系] 學位論文

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