Geographically weighted Poisson regression for disease association mapping.

@article{Nakaya2005GeographicallyWP,
  title={Geographically weighted Poisson regression for disease association mapping.},
  author={Tomoki Nakaya and A. Stewart Fotheringham and Chris Brunsdon and Martin Charlton},
  journal={Statistics in medicine},
  year={2005},
  volume={24 17},
  pages={2695-717}
}
This paper describes geographically weighted Poisson regression (GWPR) and its semi-parametric variant as a new statistical tool for analysing disease maps arising from spatially non-stationary processes. The method is a type of conditional kernel regression which uses a spatial weighting function to estimate spatial variations in Poisson regression parameters. It enables us to draw surfaces of local parameter estimates which depict spatial variations in the relationships between disease rates… CONTINUE READING
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