Statistical Inference and Simulation for Spatial Point Processes

1. Auflage 2003
ISBN: 978-1-58488-265-7
Verlag: Taylor & Francis Inc

Buch, Englisch, 318 Seiten, Format (B × H): 161 mm x 234 mm, Gewicht: 558 g

Reihe: Chapman & Hall/CRC Monographs on Statistics and Applied Probability

Spatial point processes play a fundamental role in spatial statistics and today they are an active area of research with many new applications. Although other published works address different aspects of spatial point processes, most of the classical literature deals only with nonparametric methods, and a thorough treatment of the theory and applications of simulation-based inference is difficult to find. Written by researchers at the top of the field, this book collects and unifies recent theoretical advances and examples of applications. The authors examine Markov chain Monte Carlo algorithms and explore one of the most important recent developments in MCMC: perfect simulation procedures.

Zielgruppe

Professional

Autoren/Hrsg.

Moller, Jesper (Aalborg University, Denmark)

Moller, Jesper

Waagepetersen, Rasmus Plenge (Aalborg University, Denmark)

Waagepetersen, Rasmus Plenge

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung

Inhaltsverzeichnis

Introduction. Background. Markov Chain Monte Carlo Algorithms for Spatial Point Processes. Perfect Simulation. Approximate Likelihood Inference. Simulation-Based Bayesian Inference.

Über Autor(innen)

Jesper Moller