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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Bibliographic Details
Main Author: Tiefelsdorf, Michael
Format: eBook
Language:English
Published: Berlin, Heidelberg Springer Berlin Heidelberg 2000, 2000
Edition:1st ed. 2000
Series:Lecture Notes in Earth Sciences
Subjects:
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
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245 0 0 |a Modelling Spatial Processes  |h Elektronische Ressource  |b The Identification and Analysis of Spatial Relationships in Regression Residuals by Means of Moran’s I  |c by Michael Tiefelsdorf 
250 |a 1st ed. 2000 
260 |a Berlin, Heidelberg  |b Springer Berlin Heidelberg  |c 2000, 2000 
300 |a XVIII, 167 p. 14 illus  |b online resource 
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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653 |a Econometrics 
653 |a Geography 
653 |a Statistics  
653 |a Environmental Health 
653 |a Environmental health 
653 |a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences 
653 |a Econometrics 
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490 0 |a Lecture Notes in Earth Sciences 
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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