Análise de datos reticulares
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[ES] La estadística espacial es la rama de la estadística que trata datos teniendo en cuenta su
situación y distribución en el espacio. La estadística de datos reticulares divide el espacio
en regiones o áreas discretas y estudia el efecto de variables aleatorias sobre sí mismas
(autorregresión) como consecuencia de su realización en áreas próximas.
En este documento se introduce una construcción teórica de los modelos espaciales más
utilizados para los datos reticulares centrándose en el caso gaussiano, como los modelos
simultáneamente y condicionalmente especificados. Se continúa con una relación de las
estructuras espaciales discretas utilizadas comúnmente para describir datos reticulares. En
el tercer capítulo se discuten las distintas pruebas para evaluar la existencia de dependencia
espacial. Finalmente, en el último capítulo se incluye un ejemplo práctico en el que se
construyen modelos espaciales sobre la mortalidad por cáncer de pulmón en municipios de
Galicia incluyendo los efectos de varias covariables.
[EN] Spatial statistics is the branch of statistics that processes data considering their location and distribution in space. Lattice data statistics divides space into regions or discrete areas and studies the effect of random variables on themselves (autoregression) as a consequence of their realization in nearby areas . In this document, a theoretical construction is introduced for the most usual spatial models for lattice data, such as simultaneously and conditionally specified models, focusing on the Gaussian case. It continues with an enumeration of the discrete spatial structures commonly used to describe lattice data. The third chapter discusses the different tests used to evaluate the existence of spatial dependence. Finally, the last chapter includes a practical example in which spatial models on lung cancer mortality in municipalities of Galicia are fitted taking into account the effects of several covariates.
[EN] Spatial statistics is the branch of statistics that processes data considering their location and distribution in space. Lattice data statistics divides space into regions or discrete areas and studies the effect of random variables on themselves (autoregression) as a consequence of their realization in nearby areas . In this document, a theoretical construction is introduced for the most usual spatial models for lattice data, such as simultaneously and conditionally specified models, focusing on the Gaussian case. It continues with an enumeration of the discrete spatial structures commonly used to describe lattice data. The third chapter discusses the different tests used to evaluate the existence of spatial dependence. Finally, the last chapter includes a practical example in which spatial models on lung cancer mortality in municipalities of Galicia are fitted taking into account the effects of several covariates.
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Traballo Fin de Grao en Matemáticas. Curso 2018-2019
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