Spatial and spatio-temporal point patterns on linear networks
The last decade witnessed an extraordinary increase in interest in the analysis of network related data and trajectories. In the spatial statistics field, there are numerous real examples such as the locations of traffic accidents and geo-coded locations of crimes in the streets that need to restric...
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| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2018 |
| País: | España |
| Institución: | CBUC, CESCA |
| Repositorio: | TDR. Tesis Doctorales en Red |
| OAI Identifier: | oai:www.tdx.cat:10803/664140 |
| Acceso en línea: | http://hdl.handle.net/10803/664140 http://dx.doi.org/10.6035/14123.2018.685382 |
| Access Level: | acceso abierto |
| Palabra clave: | Intensity estimator Kernel Linear network Point process Resample-smoothing Trajectory Ciències naturals, químiques, físiques i matemàtiques 52 68 |
| Sumario: | The last decade witnessed an extraordinary increase in interest in the analysis of network related data and trajectories. In the spatial statistics field, there are numerous real examples such as the locations of traffic accidents and geo-coded locations of crimes in the streets that need to restrict the support of the underlying process over such linear networks to set and define a more realistic scenario. Examples of trajectories are the path taken by moving objects such as taxis, human beings, animals, etc. This tesis provides different statistical tools to study spatial and spatio-temporal points processes on linear networks, and trajectories through first and second order summary statistics. Regarding trajectories, the developed methods are also accommodated in the R package "trajectories". |
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