Statistical Inference and Simulation for Spatial Point Processes

摘要: EXAMPLES OF SPATIAL POINT PATTERNS INTRODUCTION TO PROCESSES Point Processes on R^d Marked and Multivariate Unified Framework Space-Time POISSON Basic Properties Further Results Poisson SUMMARY STATISTICS First Second Order Summary Statistics Nonparametric Estimation for COX Definition Simple Examples Neyman-Scott as Cox Shot Noise Approximate Simulation of SNCPs Log Gaussian Fields LGCPs MARKOV Finite with a Density Pairwise Interaction Markov Extensions to Inhomogeneous METROPOLIS-HASTINGS ALGORITHMS Description Algorithms Background Material Chains Convergence SIMULATION-BASED INFERENCE Monte Carlo Methods Output Analysis Ratios Normalising Constants Likelihood Inference Using MCMC Error Distribution Estimates Hypothesis Tests MissingData Likelihoods FOR Maximum Pseudo Bayesian Minimum Contrast Conditional Prediction BIRTH-DEATH AND PERFECT SIMULATION Spatial Birth-Death Perfect APPENDICES History, Bibliography, Software Measure Theoretical Details Moment Measures Palm Distributions Nearest-Neighbour References Subject Index Notation