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Books > Science & Mathematics > Mathematics > Probability & statistics
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Spatial Statistics and Spatio-Temporal Data - Covariance Functions and Directional Properties (Hardcover)
Loot Price: R2,463
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Spatial Statistics and Spatio-Temporal Data - Covariance Functions and Directional Properties (Hardcover)
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In the spatial or spatio-temporal context, specifying the correct
covariance function is fundamental to obtain efficient predictions,
and to understand the underlying physical process of interest. This
book focuses on covariance and variogram functions, their role in
prediction, and appropriate choice of these functions in
applications. Both recent and more established methods are
illustrated to assess many common assumptions on these functions,
such as, isotropy, separability, symmetry, and intrinsic
correlation. After an extensive introduction to spatial
methodology, the book details the effects of common covariance
assumptions and addresses methods to assess the appropriateness of
such assumptions for various data structures. Key features: * An
extensive introduction to spatial methodology including a survey of
spatial covariance functions and their use in spatial prediction
(kriging) is given. * Explores methodology for assessing the
appropriateness of assumptions on covariance functions in the
spatial, spatio-temporal, multivariate spatial, and point pattern
settings. * Provides illustrations of all methods based on data and
simulation experiments to demonstrate all methodology and guide to
proper usage of all methods. * Presents a brief survey of spatial
and spatio-temporal models, highlighting the Gaussian case and the
binary data setting, along with the different methodologies for
estimation and model fitting for these two data structures. *
Discusses models that allow for anisotropic and nonseparable
behaviour in covariance functions in the spatial, spatio-temporal
and multivariate settings. * Gives an introduction to point pattern
models, including testing for randomness, and fitting regular and
clustered point patterns. The importance and assessment of isotropy
of point patterns is detailed. Statisticians, researchers, and data
analysts working with spatial and space-time data will benefit from
this book as well as will graduate students with a background in
basic statistics following courses in engineering, quantitative
ecology or atmospheric science.
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