Spatial analysis (Statistics)
Overview
            | Works: | 53 works in 23 publications in 23 languages | |
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Titles
          
                  
                    Statistical analysis of spatial and spatio-temporal point patterns
                  
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                    Spatial analysis and modeling in geographical transformation process = GIS-based applications /
                  
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                        GIS and spatial analysis for the social sciences = coding, mapping and modeling /
                      
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                        Discovery of geospatial resources = methodologies, technologies, and emergent applications /
                      
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                        Peripheralization = the making of spatial dependencies and social injustice /
                      
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                        Stochastic geometry, spatial statistics and random fields = asymptotic methods /
                      
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                        Defining the spatial scale in modern regional analysis = new challenges from data at local level /
                      
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                        Spatial AutoRegression (SAR) model = parameter estimation techniques /
                      
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                        Emerging methods and multidisciplinary applications in geospatial research
                      
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                        Spatio-temporal design DUP_1 = advances in efficient data acquisition /
                      
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                        Space-time integration in geography and GIScience = research frontiers in the US and China /
                      
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                        Stochastic geometry, spatial statistics and random fields = models and algorithms /
                      
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                        Spatial econometrics = qualitative and limited dependent variables /
                      
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                        Spatial interaction models = facility location using game theory /
                      
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                        Spatiotemporal frequent pattern mining from evolving region trajectories
                      
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                        Spatial socio-econometric modeling (SSEM) = a low-code toolkit for spatial data science and interactive visualizations using R /
                      
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                        Random networks for communication : = from statistical physics to information systems /
                      
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                        A primer for spatial econometrics = with applications in R, STATA and Python /
                      
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