Random Patterns and Structures in Spatial Data

Auteur

Radu S. Stoica is a full professor in mathematics at University of Lorraine (France). His research activity connects stochastic geometry, spatial statistics and Bayesian inference for probabilistic modeling and statistical description of random structures and patterns. The results of his work consist of tailored to the data methodologies based on Gibbs Markov models, Monte Carlo algorithms and inference procedures, that are able to characterize and detect structures and patterns that are either hidden or directly observed in the data. The tackled application domains are: astronomy, geosciences, image analysis and network sciences. Previously to his current position, Radu Stoica was associate professor at University of Lille (France). He was also worked as a researcher for INRAe Avignon (France), University Jaume I (Spain) and CWI Amsterdam (The Netherlands).

Texte du rabat

The book presents a general mathematical framework able to detect and to characterize, from a morphological and statistical perspective, patterns hidden in spatial data. The mathematical tool employed is a Gibbs point process with interaction, which permits us to reduce the complexity of the pattern.

Contenu

1. Introduction. 2. Marked point processes. 3. Applications. 4. Markov chains: notions, properties and simulation algorithms 5. Applications. 6. Mathematical tools for statistical pattern detection and characterisation. 7. Applications.