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This authored monograph presents the use of dynamic spatiotemporal
modeling tools for the identification of complex underlying
processes in conflict, such as diffusion, relocation, heterogeneous
escalation, and volatility. The authors use ideas from statistics,
signal processing, and ecology, and provide a predictive framework
which is able to assimilate data and give confidence estimates on
the predictions. The book also demonstrates the methods on the
WikiLeaks Afghan War Diary, the results showing that this approach
allows deeper insights into conflict dynamics and allows a
strikingly statistically accurate forward prediction of armed
opposition group activity in 2010, based solely on data from
preceding years. The target audience primarily comprises
researchers and practitioners in the involved fields but the book
may also be beneficial for graduate students.
The world is becoming increasingly complex, with larger quantities
of data available to be analyzed. It so happens that much of these
"big data" that are available are spatio-temporal in nature,
meaning that they can be indexed by their spatial locations and
time stamps. Spatio-Temporal Statistics with R provides an
accessible introduction to statistical analysis of spatio-temporal
data, with hands-on applications of the statistical methods using R
Labs found at the end of each chapter. The book: Gives a
step-by-step approach to analyzing spatio-temporal data, starting
with visualization, then statistical modelling, with an emphasis on
hierarchical statistical models and basis function expansions, and
finishing with model evaluation Provides a gradual entry to the
methodological aspects of spatio-temporal statistics Provides broad
coverage of using R as well as "R Tips" throughout. Features
detailed examples and applications in end-of-chapter Labs Features
"Technical Notes" throughout to provide additional technical detail
where relevant Supplemented by a website featuring the associated R
package, data, reviews, errata, a discussion forum, and more The
book fills a void in the literature and available software,
providing a bridge for students and researchers alike who wish to
learn the basics of spatio-temporal statistics. It is written in an
informal style and functions as a down-to-earth introduction to the
subject. Any reader familiar with calculus-based probability and
statistics, and who is comfortable with basic matrix-algebra
representations of statistical models, would find this book easy to
follow. The goal is to give as many people as possible the tools
and confidence to analyze spatio-temporal data.
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