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    题名: Residual Diagnostics for Covariate Effects in Spatial Point Process Models
    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: Added variable plot;Component-plus-residual plot;Generalized linear models;Partial residual plot;Point process residuals;Spatial covariates
    日期: 2013-10-01
    上传时间: 2013-12-16 18:31:58 (UTC+8)
    出版者: Taylor & Francis Inc.
    摘要: For a spatial point process model in which the intensity depends on spatial covariates, we develop graphical diagnostics for validating the covariate effect term in the model, and for assessing whether another covariate should be added to the model. The diagnostics are point-process counterparts of the well-known partial residual plots (component-plus-residual plots) and added variable plots for generalized linear models. The new diagnostics can be derived as limits of these classical techniques under increasingly fine discretization, which leads to efficient numerical approximations. The diagnostics can also be recognized as integrals of the point process residuals, enabling us to prove asymptotic results. The diagnostics perform correctly in a simulation experiment. We demonstrate their utility in an application to geological exploration, in which a point pattern of gold deposits is modeled as a point process with intensity depending on the distance to the nearest geological fault. Online supplementary materials include technical proofs, computer code, and results of a simulation study.
    關聯: Journal of Computational and Graphical Statistics 22(4), pp.886-905
    DOI: 10.1080/10618600.2012.721737
    显示于类别:[統計學系暨研究所] 期刊論文

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