Syllabus
1. spatial models on lattices, Markov random fields, Ising model, Gaussian models
2. random fields, variogram, autocovariance function
3. random measures, existence, weak and vague convergence
4. point processes, Poisson process and other examples, moment measures, Palm distribution
5. stationary point processes, Cox process, cluster processes, hard-core point processes
6. finite point processes with density, Markov point processes
7. nonhomogeneous point process, marked point processes, marking models
Annotation
Random fields and spatial models on lattices, Markov random fields. Random measures on locally compact metric spaces, moment measures, Palm distribution.
Point processes, stationarity, characteristics, Poisson process and other models of stationary point processes. Finite point processes with density, Markov point processes, inhomogeneous point processes, marked point processes.