Leverage and Influence Diagnostics for Spatial Point Processes
For a spatial point process model fitted to spatial point pattern data, we develop diagnostics for model validation, analogous to the classical measures of leverage and influence in a generalized linear model. The diagnostics can be characterized as derivatives of basic functionals of the model. The...
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Veröffentlicht in: | Scandinavian journal of statistics 2013-03, Vol.40 (1), p.86-104 |
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creator | BADDELEY, ADRIAN CHANG, YA-MEI SONG, YONG |
description | For a spatial point process model fitted to spatial point pattern data, we develop diagnostics for model validation, analogous to the classical measures of leverage and influence in a generalized linear model. The diagnostics can be characterized as derivatives of basic functionals of the model. They can also be derived heuristically (and computed in practice) as the limits of classical diagnostics under increasingly fine discretizations of the spatial domain. We apply the diagnostics to two example datasets where there are concerns about model validity. |
doi_str_mv | 10.1111/j.1467-9469.2011.00786.x |
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subjects | Average linear density Computation deletion derivative Generalized linear models Gibbs point process Gâteaux derivative Heuristic Incinerators Leverage Parametric models point process residuals Poisson point process pseudolikelihood raised incidence model residuals spatial clustering spatial covariates Spatial models Spatial points Statism Statistical estimation Statistical methods Statistical models Statistics Studies |
title | Leverage and Influence Diagnostics for Spatial Point Processes |
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