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Semiparametric approach to point source modelling in epidemiology and criminology


  • Alexandre Rodrigues
  • Peter Diggle
  • Renato Assuncao


By treating the conditional approach that was suggested by Diggle and Rowlingson as a generalized additive model, we provide a semiparametric method for point process modelling with point source interventions. We illustrate the flexibility of this approach with two applications. The first is a reanalysis of an epidemiological case-control data set in which we compare the semiparametric fit with a previously reported parametric model. The second is an application to a complex intervention in the Brazilian city of Belo Horizonte, in which we show how the installation of 60 closed-circuit television cameras has changed the spatial distribution of crimes within an area of high criminal activity. Copyright (c) 2010 Royal Statistical Society.

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  • Alexandre Rodrigues & Peter Diggle & Renato Assuncao, 2010. "Semiparametric approach to point source modelling in epidemiology and criminology," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(3), pages 533-542.
  • Handle: RePEc:bla:jorssc:v:59:y:2010:i:3:p:533-542

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    References listed on IDEAS

    1. Crainiceanu, Ciprian M. & Ruppert, David & Wand, Matthew P., 2005. "Bayesian Analysis for Penalized Spline Regression Using WinBUGS," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 14(i14).
    2. Peter Diggle & Pingping Zheng & Peter Durr, 2005. "Nonparametric estimation of spatial segregation in a multivariate point process: bovine tuberculosis in Cornwall, UK," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(3), pages 645-658.
    3. Peter Diggle & Sara Morris & Paul Elliott & Gavin Shaddick, 1997. "Regression Modelling of Disease Risk in Relation to Point Sources," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 160(3), pages 491-505.
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