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Theoretical Aspects of Spatial-Temporal Modeling (Paperback, 1st ed. 2015)
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Theoretical Aspects of Spatial-Temporal Modeling (Paperback, 1st ed. 2015)
Series: JSS Research Series in Statistics
Expected to ship within 10 - 15 working days
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This book provides a modern introductory tutorial on specialized
theoretical aspects of spatial and temporal modeling. The areas
covered involve a range of topics which reflect the diversity of
this domain of research across a number of quantitative
disciplines. For instance, the first chapter provides up-to-date
coverage of particle association measures that underpin the
theoretical properties of recently developed random set methods in
space and time otherwise known as the class of probability
hypothesis density framework (PHD filters). The second chapter
gives an overview of recent advances in Monte Carlo methods for
Bayesian filtering in high-dimensional spaces. In particular, the
chapter explains how one may extend classical sequential Monte
Carlo methods for filtering and static inference problems to high
dimensions and big-data applications. The third chapter presents an
overview of generalized families of processes that extend the class
of Gaussian process models to heavy-tailed families known as
alpha-stable processes. In particular, it covers aspects of
characterization via the spectral measure of heavy-tailed
distributions and then provides an overview of their applications
in wireless communications channel modeling. The final chapter
concludes with an overview of analysis for probabilistic spatial
percolation methods that are relevant in the modeling of graphical
networks and connectivity applications in sensor networks, which
also incorporate stochastic geometry features.
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