GWR or Geographically Weighted Regression is a local version of spatial regression that generates parameters disaggregated by the spatial units of analysis.

Geographically Weighted Regression is a local version of spatial regression that generates parameters disaggregated by the spatial units of analysis. This allows assessment of the spatial heterogeneity in the estimated relationships between the independent and dependent variables. The use of Markov Chain Monte Carlo (MCMC) methods can allow the estimation of complex functions, such as Poisson-Gamma-CAR, Poisson-lognormal-SAR, or Overdispersed logit models.

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