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    National Tsing Hua University Institutional Repository > 理學院 > 統計學研究所 > 期刊論文 >  Nonparametric prediction in species sampling

    Please use this identifier to cite or link to this item: http://nthur.lib.nthu.edu.tw/dspace/handle/987654321/54103

    Title: Nonparametric prediction in species sampling
    Authors: Chao Anne;Shen Tsung-Jen
    教師: 趙蓮菊
    Date: 2004
    Publisher: American Statistical Association Biometrics Section
    Relation: Journal of agricultural, biological, and environmental statistics,2004, vol. 9,no3, pp. 253-269
    Keywords: Nonparametric prediction
    species sampling
    Abstract: Consider a continuous-time stochastic model in which species arrive in the sample according to independent Poisson processes and where the species discovery rates are heterogeneous. Based on an initial survey, we are concerned with the problem of predicting the number of new species that would be discovered by additional sampling. When the sampling time or sample size of the additional sample tends to infinity, this problem reduces to the prediction of the number of undetected species in the original sample, or equivalently, the estimation of species richness. The topic has a wide range of applications in various disciplines. We propose a simple prediction method and apply it to two datasets. One set of data deals with the capture counts of the Malayan butterfly and the other set deals with identification records of organic pollutants in a water environment. Simulation results are shown to investigate the performance of the proposed method and to compare it with the existing estimators.
    URI: http://cat.inist.fr/?aModele=afficheN&cpsidt=22202331
    Appears in Collections:[統計學研究所] 期刊論文

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