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    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/78142

    题名: Nonparametric estimation of the dependence of a spatial point process on spatial covariates
    作者: Baddeley, Adrian;Chang, Ya-Mei;Song, Yong;Turner, Rolf
    贡献者: 淡江大學統計學系
    关键词: confidence intervals;density estimation;kernel smoothing;local likelihood;logistic regression;point process intensity;poisson point process;[geological] prospectivity mapping;spatial covariates;relative distributions;resource selection function;weighted distribution
    日期: 2012-06
    上传时间: 2012-09-05 16:54:12 (UTC+8)
    出版者: Somerville: International Press
    摘要: In the statistical analysis of spatial point patterns, it is often important to investigate whether the point pattern depends on spatial covariates. This paper describes nonparametric (kernel and local likelihood) methods for estimating the effect of spatial covariates on the point process intensity. Variance estimates and confidence intervals are provided in the case of a Poisson point process. Techniques are demonstrated with simulated examples and with applications to exploration geology and forest ecology.
    關聯: Statistics and Its Interface 5(2), pp.221-236
    DOI: 10.4310/SII.2012.v5.n2.a7
    显示于类别:[統計學系暨研究所] 期刊論文


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