Modelling Spatial Processes

The Identification and Analysis of Spatial Relationships in Regression Residuals by Means of Moran’s I

Nonfiction, Science & Nature, Science, Earth Sciences, Geography, Health & Well Being, Medical, Reference, Public Health
Cover of the book Modelling Spatial Processes by Michael Tiefelsdorf, Springer Berlin Heidelberg
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Author: Michael Tiefelsdorf ISBN: 9783540486770
Publisher: Springer Berlin Heidelberg Publication: April 11, 2006
Imprint: Springer Language: English
Author: Michael Tiefelsdorf
ISBN: 9783540486770
Publisher: Springer Berlin Heidelberg
Publication: April 11, 2006
Imprint: Springer
Language: English
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.
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
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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