Journal of Statistical Software · 2015 · 451 citations · 57 references
Spatial ScienceQuantitative Spatial ModelSpatial Statistical AnalysisWindow Weighting TechniqueSpatio-temporal ModelGeographyR Package GwmodelGeographic Information SciencesSocial SciencesSpatial DemographySpatial ModelingPublic HealthFunctional Data AnalysisStatisticsSpatial Statistics
Spatial statistics is a growing discipline that offers analytical techniques across natural and social sciences, and geographically weighted models address situations where global models are inadequate by providing localized calibration. GWmodel is an R package that presents techniques from geographically weighted models. It implements a moving‑window weighting approach to fit localized models at target locations and provides functions for GW summary statistics, principal components analysis, regression, and discriminant analysis in both basic and robust forms. The package maps outputs to visualize spatial heterogeneity, offering an exploratory tool for data analysis.
Spatial statistics is a growing discipline providing important analytical techniques in a wide range of disciplines in the natural and social sciences. In the R package GWmodel we present techniques from a particular branch of spatial statistics, termed geographically weighted (GW) models. GW models suit situations when data are not described well by some global model, but where there are spatial regions where a suitably localized calibration provides a better description. The approach uses a moving window weighting technique, where localized models are found at target locations. Outputs are mapped to provide a useful exploratory tool into the nature of the data spatial heterogeneity. Currently, GWmodel includes functions for: GW summary statistics, GW principal components analysis, GW regression, and GW discriminant analysis; some of which are provided in basic and robust forms.
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R: A Language and Environment for Statistical Computing
R Core Team · 2000 · 352.8K citations · Full text