Modelling spatial processes: the identification and analysis of spatial relationships in regression residuals by means of Moran's I [Libro electrónico] / autor: Michael Tiefelsdorf
Por: Tiefelsdorf, Michael [autor/a].
Tipo de material: Libro en línea Series Editor: New York, New York, United States: Springer-Verlag, c2000Descripción: xviii, 167 páginas : ilustraciones mapas ; 24 centímetros.ISBN: 3540662081; 9783540662082 (Print); 9783540486770 (Online).Tema(s): Spatial analysis (Statistics) | Regression analysisNota de acceso: Disponible para usuarios de ECOSUR con su clave de acceso Nota de bibliografía: Incluye bibliografía e índice: páginas 153-161 Número de sistema: 55791Contenidos:Mostrar Resumen:Tipo de ítem | Biblioteca actual | Colección | Signatura | Estado | Fecha de vencimiento | Código de barras |
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Libros | Biblioteca Electrónica Recursos en línea (RE) | Acervo General | Recurso digital | ECO400557918365 |
Incluye bibliografía e índice: páginas 153-161
1. Introduction.. 2. The regression model.. 3. The specification of spatial relations.. 4. Gaussian spatial processes.. 5. The characteristic function.. 6. Numerical evaluation of Imhof's formula.. 7. The exact distribution of Moran's I .. 8. The shape of Moran's I exact distribution.. 9. The moments of Moran's I .. 10. The basic ecological model and spatial setting.. 11. A spatial analysis of the cancer data.. 12. Conclusions.. Index
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A novel methodology is put forward in this book, which empowers researchers to investigate and identify potential spatial processes among a set of regions. Spatial processes and their underlying functional spatial relationships are commonly observed in the geosciences and related disciplines. Examples are spatially autocorrelated random variables manifesting themselves in distinct global patterns as well as local clusters and hot spots, or spatial interaction leading to stochastic ties among the regions. An example from observational epidemiology demonstrates the flexibility of Moran's approach by analyzing the spatial distribution of cancer data from several perspectives. Recent advances in computing technology, computer algorithms, statistical techniques and global and local spatial patterns by means of Moran's I feasability. Moran's I is an extremely versatile tool for exploring and analyzing spatial data and testing spatial hypotheses. eng
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