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    政大機構典藏 > 商學院 > 統計學系 > 學位論文 >  Item 140.119/30930
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/30930


    Title: 排列檢定法應用於空間資料之比較
    Permutation test on spatial comparison
    Authors: 王信忠
    Wang, Hsin-Chung
    Contributors: 蔡紋琦
    王信忠
    Wang, Hsin-Chung
    Keywords: 費雪(Fisher)正確檢定
    Cramer-von Mises 統計量
    排列檢定
    可交換性
    空間分佈
    貝氏(Bayesian)方法
    檢定力比較
    空間自我迴歸(CAR)模型
    auto-Poisson模型
    auto-Gaussian模型
    群聚
    Fisher's exact test
    Cramer-von Mises statistic
    permutation test
    exchangeable
    spatial distributions
    Bayesian approach
    power comparison
    spatial conditionally autoregressive (CAR) model
    auto-Poisson model
    auto-Gaussian model
    cluster
    Date: 2005
    Issue Date: 2009-09-14
    Abstract: 本論文主要是探討在二維度空間上二母體分佈是否一致。我們利用排列
    (permutation)檢定方法來做比較, 並藉由費雪(Fisher)正確檢定方法的想法而提出重標記 (relabel)排列檢定方法或稱為費雪排列檢定法。
    我們透過可交換性的特質證明它是正確 (exact) 的並且比 Syrjala (1996)所建議的排列檢定方法有更高的檢定力 (power)。
    本論文另提出二個空間模型: spatial multinomial-relative-log-normal 模型 與 spatial Poisson-relative-log-normal 模型
    來配適一般在漁業中常有的右斜長尾次數分佈並包含很多0 的空間資料。另外一般物種可能因天性或自然環境因素像食物、溫度等影響而有群聚行為發生, 這二個模型亦可描述出空間資料的群聚現象以做適當的推論。
    This thesis proposes the relabel (Fisher's) permutation test inspired by Fisher's exact test to compare between distributions of two (fishery) data sets locating on a two-dimensional lattice. We show that the permutation test given by Syrjala (1996} is not exact, but our relabel permutation test is exact and, additionally, more powerful.
    This thesis also studies two spatial models: the spatial multinomial-relative-log-normal model and the spatial
    Poisson-relative-log-normal model. Both models not only exhibit characteristics of skewness with a long right-hand tail and of high proportion of zero catches which usually appear in fishery data, but also have the ability to describe various types of aggregative behaviors.
    Reference: Aitchison, J. and Ho, C. H. (1989), “The multivariate Poisson-log normal distribution.”,Biometrika, 76, 643–653.
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    Anderson, T.W. and Darling, D.A. (1952), “Asymptotic Theory of Certain ”Goodness of Fit” Criteria Based on Stochastic Processes.”, The Annals of Mathematical Statistics,23, 193–212.
    Armistead, C.E. and Nichol, D.G. (1993), “1990 Bottom trawl survey of the eastern Bering Sea continental shelf.”, United States Department of Commerce,NOAA Technical Mem-orandum NMFS-AFSC-7.
    Besag, J.E. (1974), “Spatial interaction and statistical analysis of lattice systems.”, Journal of the Royal Society B, 36, 192–225.
    Brodeur, R.D., Sugisaki, H., and Hunt, G. L. (2002), “Increases in jellyfish biomas in the bering sea: implications for the ecosystem.”, Marine Ecology Process Series ., 233,89–103.
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    Hedger, R., McKenzie, E., Heath, M., Wright, P., Scott, B., Gallego, A., and Andrews, J. (2004), “Analysis of the spatial distributions of mature cod (gadus morhua) and haddock (melanogrammus aeglefinus) abundance in the north sea (1980-1999) using generalised additive models.”, Fisheries Research., 70, 17–25.
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    Swain, D.P. and Wade, E.J. (2003), “Spatial distribution of catch and effort in a fishery for snow crab (Chionoecetes opilio): tests of predictions of the ideal free distribution.”,Can J. Fish. Aquat. Sci., 60, 897–909.
    Syrjala, S.E. (1996), “A statistical test for a difference between the spatial distribution of two populations”, Ecology, 77(1), 75–80.
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    Bulletin., 10, 61–77.62
    Description: 博士
    國立政治大學
    統計研究所
    90354503
    94
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0903545031
    Data Type: thesis
    Appears in Collections:[統計學系] 學位論文

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