Spatial cluster modelling

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