English  |  正體中文  |  简体中文  |  Items with full text/Total items : 51931/87076 (60%)
Visitors : 8487358      Online Users : 97
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/95656


    Title: 相關性資料之頻率分析:合成資料研究
    Other Titles: Frequency Analysis of Correlated Data:Synthetic Data Study
    Authors: 虞國興;林慶杰
    Contributors: 淡江大學水資源及環境工程學系
    Keywords: 頻率分析;極值理論;偏態係數;機率點繪相關係數檢定法;Frequency Analysis;Extreme Value Theory;Skewness Coefficient;Probability Plot Correlation Coefficient Test
    Date: 1994-12
    Issue Date: 2014-02-12 20:33:52 (UTC+8)
    Publisher: 臺北市:行政院農業委員會
    Abstract: 本研究以合成資料探討當資料不滿足極端 值理論之兩項基本假設:(1)族群內資料須屬同 一機率分布且相互獨立,及(2)族群內資料樣本 數需趨近無限大,時對極端值I型分布之適用性 。研究中採用機率點繪相關係數檢定 ( Probability plot correlation coefficient test)法,藉其能 正確反映I型誤差(Type I error)之特性,由通過檢 定之組數是否合理,探討相關性資料於極端值I 型分布之適用性及其應用時之效力。 研究結果顯示,資料之相關性愈強,極端值I 型分布愈不適用;即使當族群內樣本數為365時, 亦不保證極端值I型分布適用,主要因受族群內 資料偏態係數影響。同時,當族群內資料之偏 態係數接近極端值I型分布理論偏態係數值1.139 時,不論相關性及族群內之樣本數大小,極端值I 型分布皆適用。另,機率點繪相關係數檢定法 應用於極端值I型分布時其效力遠較K.S.檢定為 佳。
    The aptness of extreme value type I distribution for the data which do not satisfy the basic assumptions of extreme value theory is investigated by synthetic data in the present study. The basic assumptions are that (1) data within group obey the same probability density function and do not mutually depend each other, and (2) the sample size of each group should approaches infinite. The probability plot correlation coefficient test is employed in this study. This is done by judging whether the percentage of rejecting the null hypothesis is reasonable, since this test preserves the type I error. The results indicates that extreme value type I distribution is not appropriate when the data are highly correlated, and even when the sample size of each group is 365. The major influence factor is the skewness coefficient of data for each group. Meanwhile, no mater how strong the correlation is and how large the sample size of data within group is, extreme value type I distribution is always appropriate whenever the skewness coefficient of data within group is close to 1.139 which is the theoretical skewness coefficient of extreme type I distribution. Besides, the results indicates that the probability plot coefficient test is more powerful than K.S. test.
    Relation: 八十三年度農業工程研討會論文集,頁177-189
    Appears in Collections:[水資源及環境工程學系暨研究所] 會議論文

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML94View/Open
    相關性資料之頻率分析.docx摘要13KbMicrosoft Word91View/Open
    相關性資料之頻率分析_西文摘要.docx摘要13KbMicrosoft Word59View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback