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This thesis has the objective of systematizing the use of spatial statistical models for use in the planning of services, through the use of computational tools that allow the construction of those models. From a bibliographical revision the criteria used in the planning of the services was presented, pertinent concepts to the statistical analysis of spatial data and the interaction among those topics. Too explorer the creation of a spatial database pertinent to the analysis are presented and the computational tools that make possible the application of the techniques developed in this thesis, with emphasis in the R Language and its packages of spatial analysis. The following tools are presented: GeoDa, TerraView and TerraCrime.In the sequence, the applicable analysis techniques to spatial phenomena are explored modeled by points and for areas, denominated, respectively point process and areas process. Exploratory or descriptive techniques are presented to verify the forms of visualization of the data, the distribution type or the existence of groupings. Also, inferential techniques are presented to model and to quantify spatial dependence, to estimate surfaces and the estimation of models of spatial regression. Each technique is exemplified through the computational tools presented.To exemplify, a practical application of techniques of spatial statistical analysis is presented with data from public safety, where factors are identified associated with crime rates through the use of spatial regression.To conclude the work, the requirements that should be taken into consideration in the construction of a computational environmental that allow for the analysis of spatial data are presented. Also, each spatial statistical method explored in the planning of services was analyzed, as well as the results of the application in the Public Safety area. |
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