Spatial Statistics

Author: Jürgen Symanzik. Version: September 20, 2000

In spatial statistics, we deal with spatial data, i.e., data collected in a particular region such as a country, multiple states, etc. Examples for such data sets are economic data, environmental data, or medical data. For spatial data, we should typically consider a spatial correlation. Often, observations from nearby locations are where similar. The field of spatial statistics provides techniques that allow to deal with spatially correlated data. In this tutorial, we describe the use of XploRe's spatial statistics quantlets.

At this stage, XploRe supports two areas of specialization within spatial statistics: (i) Spatial interpolation, smoothing, and kriging; and (ii) Spatial point process analysis. Quantlets related to (i) start with the letters SPKR and quantlets related to (ii) with SPPP.

Even a basic introduction into spatial statistics is far beyond the limits of this tutorial. For a detailed overview of spatial statistics, the reader is referred to Ripley (1981) or Cressie (1993), for example.



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