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GIS-based analytical tools for transport planning: spatial regression models for transportation demand forecast
(2014)
Considering the importance of spatial issues in transport planning, the main objective of this study was to analyze the results obtained from different approaches of spatial regression models. In the case of spatial ...
Modeling vague spatial data warehouses using the VSCube conceptual model
(SpringerDordrecht, 2014-04)
Although many real world phenomena are vague and characterized by having uncertain location or vague shape, existing spatial data warehouse models do not support spatial vagueness and then cannot properly represent these ...
The Spatial Dependence in Central Sulawesi Province
(Universidad del Zulia, 2019)
A non-homogeneous poisson model with spatial anisotropy applied to ozone data from Mexico City
(Springer, 2015-06-01)
In this work we consider a non-homogenous Poisson model to study the behaviour of the number of times that a pollutant's concentration surpasses a given threshold of interest. Spatial dependence is imposed on the ...
Peru's Regional Growth and Convergence in 1979-2017: An Empirical Spatial Panel Data Analysis
(Pontificia Universidad Católica del Perú. Departamento de EconomíaPE, 2021)
Spatial confounding beyond generalized linear mixed models: extension to shared components and spatial frailty models
(Universidade Federal de Minas GeraisBrasilICX - DEPARTAMENTO DE ESTATÍSTICAPrograma de Pós-Graduação em EstatísticaUFMG, 2020-02-28)
Spatial confounding is the name given to the confounding between fixed and spatial random effects in generalized linear mixed models (GLMMs). It has been widely studied and it gained attention in the past years in the ...