Abstract
We give an overview of the papers published in this special issue on spatial statistics, of the Journal of Statistical Software. 21 papers address issues covering visualization (micromaps, links to Google Maps or Google Earth), point pattern analysis, geostatistics, analysis of areal aggregated or lattice data, spatio-temporal statistics, Bayesian spatial statistics, and Laplace approximations. We also point to earlier publications in this journal on the same topic.
Highlights
As a reaction to the steadily growing availability of open source software for spatial statistics, the success of the Journal of Statistical Software, and the need for papers on scientific software in general, in February 2013 we issued a call for papers for a special issue on spatial statistics
This may be either because the special issue call was best circulated among R users and developers, or perhaps because most scientific software about spatial statistics is currently being developed in R
Earlier papers published in the Journal of Statistical Software on the topic of geostatistics include Barry (1996) — the first paper published in the Journal, Finley, Banerjee, and Carlin (2007); Smith, Yan, and Cowles (2008); Davies and Bryant (2013); Peterson and Ver Hoef (2014) and Ver Hoef, Peterson, Clifford, and Shah (2014)
Summary
As a reaction to the steadily growing availability of open source software for spatial statistics, the success of the Journal of Statistical Software, and the need for papers on scientific software in general, in February 2013 we issued a call for papers for a special issue on spatial statistics. In total, 21 papers submitted to this call were accepted, and are bundled in this special issue. 21 papers submitted to this call were accepted, and are bundled in this special issue The papers in this issue largely focus on packages for the R system for statistical computing (R Core Team 2014). This may be either because the special issue call was best circulated among R users and developers, or perhaps because most scientific software about spatial statistics is currently being developed in R. We will briefly discuss the contributions in this special issue under their sub-area visualization, point patterns, geostatistics, and lattice or areal data, and mention with each paper whether they involve Bayesian methods and spatio-temporal processes
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