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Books > Science & Mathematics > Biology, life sciences > Life sciences: general issues
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Spatial Relationships Between Two Georeferenced Variables - With Applications in R (Hardcover, 1st ed. 2020)
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Spatial Relationships Between Two Georeferenced Variables - With Applications in R (Hardcover, 1st ed. 2020)
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This book offers essential, systematic information on the
assessment of the spatial association between two processes from a
statistical standpoint. Divided into eight chapters, the book
begins with preliminary concepts, mainly concerning spatial
statistics. The following seven chapters focus on the methodologies
needed to assess the correlation between two or more processes;
from theory introduced 35 years ago, to techniques that have only
recently been published. Furthermore, each chapter contains a
section on R computations to explore how the methodology works with
real data. References and a list of exercises are included at the
end of each chapter. The assessment of the correlation between two
spatial processes has been tackled from several different
perspectives in a variety of applications fields. In particular,
the problem of testing for the existence of spatial association
between two georeferenced variables is relevant for posterior
modeling and inference. One evident application in this context is
the quantification of the spatial correlation between two images
(processes defined on a rectangular grid in a two-dimensional
space). From a statistical perspective, this problem can be handled
via hypothesis testing, or by using extensions of the correlation
coefficient. In an image-processing framework, these extensions can
also be used to define similarity indices between images.
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