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Introducing R
  • Spatial and displaying some geographic data including
  • Geostatistical data using simple maps
  • Lattice
  • Visualization of point
Point Pattern Analysis
  • Dealing with non-homogeneity using the spatstat package
  • Global tests against the hypothesis of complete spatial randomness
  • Kernel density estimation
Area (lattice) objects
  • Spatial autocorrelation and local statistics including
  • Geographically weighted regression using the spdep package
  • Global autocorrelation,
  • Local indicators of spatial association
Geostatistical data
  • The analysis of continuous ‘field’ data by variography including
  • Interpolation by the inverse distance decay
  • Kriging using the gstat package
  • Trend surface analysis
  • Variography

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