Spatial point processes are mathematical models used to describe
and analyse the geometrical structure of patterns formed by objects
that are irregularly or randomly distributed in one-, two- or
three-dimensional space. Examples include locations of trees in a
forest, blood particles on a glass plate, galaxies in the universe,
and particle centres in samples of material.
Numerous aspects of the nature of a specific spatial point
pattern may be described using the appropriate statistical methods.
Statistical Analysis and Modelling of Spatial Point Patterns
provides a practical guide to the use of these specialised methods.
The application-oriented approach helps demonstrate the benefits of
this increasingly popular branch of statistics to a broad
audience.
The book:
* Provides an introduction to spatial point patterns for
researchers across numerous areas of application
* Adopts an extremely accessible style, allowing the
non-statistician complete understanding
* Describes the process of extracting knowledge from the data,
emphasising the marked point process
* Demonstrates the analysis of complex datasets, using applied
examples from areas including biology, forestry, and materials
science
* Features a supplementary website containing example
datasets.
Statistical Analysis and Modelling of Spatial Point
Patterns is ideally suited for researchers in the many areas of
application, including environmental statistics, ecology, physics,
materials science, geostatistics, and biology. It is also suitable
for students of statistics, mathematics, computer science, biology
and geoinformatics.
Sobre o autor
Janine Illian, SIMBIOS, University of Abertay, Dundee, Scotland.
Antti Pentinen, Professor in the Department of Mathematics and Statistics, University of Jyvaskyla, Finland.
Dietrich Stoyan, Professor a the Insitut für Stochastik, University of Freiberg, Germany.
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