Selected article for: "Data analysis and open source"

Author: Wang, Jin-Feng; Christakos, George; Han, Wei-Guo; Meng, Bin
Title: Data-driven exploration of ‘spatial pattern-time process-driving forces’ associations of SARS epidemic in Beijing, China
  • Document date: 2008_4_26
  • ID: 2nko37oo_50
    Snippet: More than one statistics have to be calculated in epidemic data analysis, so more resources are needed to improve the accuracy of such calculations. Fortunately, there is a plethora of computer software and open source codes that are easily accessible on the Internet and greatly facilitate data analysis computations. In this study, the datasets are managed by the GIS software ARCGIS (http://www. esri.com/software/arcgis/). The hierarchical cluste.....
    Document: More than one statistics have to be calculated in epidemic data analysis, so more resources are needed to improve the accuracy of such calculations. Fortunately, there is a plethora of computer software and open source codes that are easily accessible on the Internet and greatly facilitate data analysis computations. In this study, the datasets are managed by the GIS software ARCGIS (http://www. esri.com/software/arcgis/). The hierarchical clustering is implemented by the Crimestat software (http://www.icpsr. umich.edu/CRIMESTAT/). Moran's coefficient I M is calculated using the GeoDA software (http://www.geoda.uiuc. edu/). Wavelet decomposition and SSEIR are computed using Matlab (http://www.icpsr.umich.edu/CRIMESTAT/), and the BW test is performed using software compiled by the authors. Primary training on GIS and spatial statistics are needed in order to operate the above software.

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