SubjectsSubjects(version: 945)
Course, academic year 2016/2017
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Point Processes - NMAT011
Title: Bodové procesy
Guaranteed by: Mathematical Institute of Charles University (32-MUUK)
Faculty: Faculty of Mathematics and Physics
Actual: from 2011 to 2017
Semester: summer
E-Credits: 3
Hours per week, examination: summer s.:2/0, Ex [HT]
Capacity: unlimited
Min. number of students: unlimited
4EU+: no
Virtual mobility / capacity: no
State of the course: not taught
Language: Czech
Teaching methods: full-time
Teaching methods: full-time
Guarantor: prof. RNDr. Jan Rataj, CSc.
Class: DS, pravděpodobnost a matematická statistika
Classification: Mathematics > Probability and Statistics, Topology and Category
Is incompatible with: NMTP564
Annotation -
Last update: T_KPMS (22.05.2008)
Random measures on locally compact spaces, point processes as integer-valued random measures, existence and uniqueness results, Poisson processes, moment measures and the Laplace functional, Palm distribution, convergence of point processes, stationary point processes in $R^d$, point processes on the set of compact subsets of $R^d$, the Boolean model, exterior conditioning. Literature: (1) D.J.Daley, D.Vere-Jones: An Introduction to the Theory of Point Processes (Springer, 1988) (2) O.Kallenberg: Random Measures (Akademie-Verlag Berlin, 1983) (3) D.Stoyan, W.S.Kendall, J.Mecke: Stocha
Aim of the course -
Last update: T_KPMS (22.05.2008)

To explain mathematical foundations of stochastic geometry.

Literature -
Last update: T_KPMS (22.05.2008)

Literature:

(1) D.J.Daley, D.Vere-Jones: An Introduction to the Theory of Point Processes

(Springer, 1988)

(2) O.Kallenberg: Random Measures (Akademie-Verlag Berlin, 1983)

(3) D.Stoyan, W.S.Kendall, J.Mecke: Stocha

Teaching methods -
Last update: G_M (29.05.2008)

Lecture.

Syllabus -
Last update: T_MUUK (23.05.2003)

1. Random measures and point processes on locally compact spaces. 2. Existence of processes with given finite dimensional distributions. 3. Intensity measure, moment measures, Laplace functional. 4. Palm distribution of a point process. 5. Poisson point process and Boolean model. 6. Weak convergence of point processes. 7. Gibbs point processes.

 
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