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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