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Full Description
Research has generated a number of advances in methods for spatial cluster modelling in recent years, particularly in the area of Bayesian cluster modelling. Along with these advances has come an explosion of interest in the potential applications of this work, especially in epidemiology and genome research.
In one integrated volume, this book reviews the state-of-the-art in spatial clustering and spatial cluster modelling, bringing together research and applications previously scattered throughout the literature. It begins with an overview of the field, then presents a series of chapters that illuminate the nature and purpose of cluster modelling within different application areas, including astrophysics, epidemiology, ecology, and imaging. The focus then shifts to methods, with discussions on point and object process modelling, perfect sampling of cluster processes, partitioning in space and space-time, spatial and spatio-temporal process modelling, nonparametric methods for clustering, and spatio-temporal cluster modelling.
Many figures, some in full color, complement the text, and a single section of references cited makes it easy to locate source material. Leading specialists in the field of cluster modelling authored each chapter, and an introduction by the editors to each chapter provides a cohesion not typically found in contributed works. Spatial Cluster Modelling thus offers a singular opportunity to explore this exciting new field, understand its techniques, and apply them in your own research.
Contents
Spatial Cluster Modelling: An Overview. POINT PROCESS CLUSTER MODELLING: Significance in Scale-Space for Clustering. Statistical Inference for Cox Processes. Extrapolating and Interpolating Spatial Patterns. Perfect Sampling for Point Process Cluster Modelling. Bayesian Estimation and Segmentation of Spatial Point Processes Using Voronoi Tilings. SPATIAL PROCESS CLUSTER MODELLING: Partition Modelling. Cluster Modelling for Disease Rate Mapping. Analyzing Spatial Data Using Skew-Gaussian Processes. Accounting for Absorption Lines In Images Obtained With The Chandra X-Ray Observatory. Spatial Modelling of Count Data: A Case Study in Modelling Breeding Bird Survey Data on Large Spatial Domains. SPATIO-TEMPORAL CLUSTER MODELLING: Modelling Strategies for Spatial-Temporal Data. Spatio-Temporal Partition Modelling: An Example FROM Neurophysiology. Spatio-Temporal Cluster Modelling of Small Area Health Data. References. Index. Author Index.
