This is the second of five chapters on "Spatial Modeling I" from the user manual for CrimeStat IV, a spatial statistics package that can analyze crime incident location data.
This chapter, "Head-Bang Interpolation," describes the Head-Bang routine and the Interpolated Head-Bang routine. The Head-Bang statistic is a weighted two-dimensional smoothing algorithm that is applied to zonal (polygon) data, such as census tracts, traffic analysis zones, or zip codes. Unlike other smoothing techniques, such as kernel density interpolation, the Head-Bang is designed to remove small-scale local variations within a data set while preserving regional trends. It is particularly useful when there are large differences in the population sizes of the different zones, which can lead to significant variability in the rates over the study area. The aim of the Head-Bang statistic is to smooth out the values for smaller geographical zones while generally keeping the values for larger geographical zones. The Head-Bang algorithm used in CrimeStat is a simplification of the methodology proposed by Mungiole, Pickle, and Simonson (2002), but similar to that used by Pickle and Su (2002). This chapter identifies and discusses the three elements to the data that are relevant to the Head-Bang. Examples of the uses of the Head-Bang are for mapping burglaries and burglary rates in Houston, Texas. The Head-Bang calculations can be interpolated to a grid. If the user checks this box, then the routine will also interpolate the calculations to a grid, using kernel density estimation. An output file from the Head-Bang routine is required. Also, a reference file is required to be defined. This procedure is described in detail in this chapter and is applied to the previous example in visualizing Houston burglaries. 13 references and extensive figures that include computer screens and maps for the examples
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- BJA Crime Analysis Consortium Resources