Modelling spatial processes : the identification and analysis of spatial relationships in regression residuals by means of Moran's I

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. Exampl...

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Glavni avtor: Tiefelsdorf, Michael, 1958-
Format: Livre numérique
Jezik:Anglais
Izdano: Berlin [etc.] : Springer [20..].
Cham : Springer Nature
Serija:Lecture notes in Earth sciences 87
Teme:
Online dostop:Accès sur la plateforme de l'éditeur
Accès sur la plateforme Istex
Accès Université d'Orléans
Accès INSA CVL
Sporočilo: Archives Springer e-books (Licence nationale)
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Edition sous un autre format:• Modelling spatial processes, the identification and analysis of spatial relationships in regression residuals by means of Moran's I, Michael Tiefelsdorf, Berlin, Springer, 2000, 1 vol. (xviii-167 p.), Lecture notes in earth sciences, 978-3-540-66208-2
• Modelling Spatial Processes, Texte imprimé, 9783662170434
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505 0 |a The regression model -- The specification of spatial relations -- Gaussian spatial processes -- The characteristic function -- Numerical evaluation of Imhof's formula -- The exact distribution of Moran's I -- The shape of Moran's I exact distribution -- The moments of Moran's I -- The basic ecological model and spatial setting -- A spatial analysis of the cancer data -- Conclusions. 
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520 |a 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. 
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