Statistical Inference and Simulation for Spatial Point Processes

Delve into the intricate world of spatial point processes with Statistical Inference and Simulation for Spatial Point Processes by Jesper Moller, published by Taylor & Francis Inc in 2003. Spanning 318 pages, this comprehensive hardback offers a thorough examination of simulation-based inference techniques that are pivotal in understanding complex data structures in spatial statistics.

The book places a strong emphasis on Markov Chain Monte Carlo (MCMC) methods and explores both Cox and Markov point processes in detail. Moller provides a rigorous treatment of MCMC techniques, which are essential for statistical inference, making this volume an invaluable resource for researchers and practitioners alike. Whether you're a statistician, mathematician, or simply interested in the field of spatial analysis, Moller’s insights will enhance your understanding and application of these sophisticated methodologies.