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    National Tsing Hua University Institutional Repository > 理學院 > 統計學研究所 > 期刊論文 >  A Two-Stage Probabilistic Approach to Multiple-Community Similarity Indices


    Please use this identifier to cite or link to this item: http://nthur.lib.nthu.edu.tw/dspace/handle/987654321/54112


    Title: A Two-Stage Probabilistic Approach to Multiple-Community Similarity Indices
    Authors: Chao, Anne;Jost, Lou;Chiang, S. C.;Jiang, Y. -H.;Chazdon, Robin L.
    教師: 趙蓮菊
    Date: 2008
    Publisher: Wiley-Blackwell
    Relation: BIOMETRICS,Volume: 64,Issue: 4,Pages: 1178-1186,Published: DEC 2008
    Keywords: SPECIES-DIVERSITY
    OVERLAP
    ESTIMATOR
    EVENNESS
    FORESTS
    Abstract: A traditional approach for assessing similarity among N (N > 2) communities is to use multiple pairwise comparisons. However, pairwise similarity indices do not completely characterize multiple-community similarity because the information shared by at least three communities is ignored. We propose a new and intuitive two-stage probabilistic approach, which leads to a general framework to simultaneously compare multiple communities based on abundance data. The approach is specifically used to extend the commonly used Morisita index and NESS (normalized expected species shared) index to the case of N communities. For comparing N communities, a profile of N - 1 indices is proposed to characterize similarity of species composition across communities. Based on sample abundance data, nearly unbiased estimators of the proposed indices and their variances are obtained. These generalized NESS and Morisita indices are applied to comparison of three size classes of plant data (seedling, saplings, and trees) within old-growth and secondary rain forest plots in Costa Rica
    URI: http://as.wiley.com/WileyCDA/Brand/id-35.html
    http://nthur.lib.nthu.edu.tw/dspace/handle/987654321/54112
    Appears in Collections:[統計學研究所] 期刊論文

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