Spatial cluster modelling

SPATIAL CLUSTER MODELLING: AN OVERVIEW Introduction Historical Development Notation and Model Development I. POINT PROCESS CLUSTER MODELLING SIGNIFICANCE IN SCALE-SPACE FOR CLUSTERING Introduction Overview New Method Future Directions STATISTICAL INFERENCE FOR COX PROCESSES Introduction Poisson Processes Cox Processes Summary Statistics Parametric Models of Cox Processes Estimation for Parametric Models of Cox Processes Prediction Discussion EXTRAPOLATING AND INTERPOLATING SPATIAL PATTERNS Introduction Formulation and Notation Spatial Cluster Processes Bayesian Cluster Analysis Summary and Conclusion PERFECT SAMPLING FOR POINT PROCESS CLUSTER MODELLING Introduction Bayesian Cluster Model Sampling from the Posterior Specialized Examples Leukemia Incidence in Upstate New York Redwood Seedlings Data BAYESIAN ESTIMATION AND SEGMENTATION OF SPATIAL POINT PROCESSES USING VORONOI TILINGS Introduction Proposed Solution Framework Intensity Estimation Intensity Segmentation Examples Discussion II. SPATIAL PROCESS CLUSTER MODELLING PARTITION MODELLING Introduction Partition Models Piazza Road Dataset Spatial Count Data Discussion Further Reading CLUSTER MODELLING FOR DISEASE RATE MAPPING Introduction Statistical Model Posterior Calculation Example: U.S. Cancer Mortality Atlas Conclusions ANALYZING SPATIAL DATA USING SKEW-GAUSSIAN PROCESSES Introduction Skew-Gaussian Processes Real Data Illustration: Spatial Potential Data Prediction Discussion ACCOUNTING FOR ABSORPTION LINES IN IMAGES OBTAINED WITH THE CHANDRA X-RAY OBSERVATORY Statistical Challenges of the Chandra X-Ray Observatory Modeling the Image Absorption Lines Spectral Models with Absorption Lines Discussion SPATIAL MODELLING OF COUNT DATA: A CASE STUDY IN MODELLING BREEDING BIRD SURVEY DATA ON LARGE SPATIAL DOMAINS Introduction The Poisson Random Effects Model Results Conclusion III. SPATIO-TEMPORAL CLUSTER MODELLING MODELLING STRATEGIES FOR SPATIAL-TEMPORAL DATA Introduction Modelling Strategy D-D (Drift-Drift) Models D-C (Drift-Correlation) Models C-C (Correlation-Correlation) Models A Unified Analysis on the Circle Discussion SPATIO-TEMPORAL PARTITION MODELLING: AN EXAMPLE FROM NEUROPHYSIOLOGY Introduction The Neurophysiological Experiment The Linear Inverse Solution The Mixture Model Classification of the Inverse Solution Discussion SPATIO-TEMPORAL CLUSTER MODELLING OF SMALL AREA HEALTH DATA Introduction Basic Cluster Modelling Approaches A Spatio-Temporal Hidden Process Model Model Development The Posterior Sampling Algorithm Data Example: Scottish Birth Abnormalities Discussion REFERENCES INDEX AUTHOR INDEX