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XP01BOP	Point processes
Roles:		Extent of teaching:	2+2
Department:	13101	Language of teaching:
Guarantors:	Helisová K.	Completion:	ZK
Lecturers:	Helisová K.	Credits:	4
Tutors:	Helisová K.	Semester:	L,Z

Web page:

http://math.feld.cvut.cz/helisova/01XP01BOP.html

Anotation:

Students get the basic overview on the theory of point processes, their probabilistic models, statistical analyses and applications.

Course outlines:

1.		Introduction to point processes
2.		Poisson point processes
3.		Summary statistics
4.		Cox processes
5.		Cluster point processes
6.		Hard-core point processes
7.		Point processes given by a density
8.		Markov point processes
9.		Gibbs processes
10.		MCMC simulations
11.		Simulation-based inference
12.		Maximum likelihood for point processes
13.		Pseudo likelihood
14.		Takacs-Fiksel method

Exercises outline:

1.		Introduction to point processes
2.		Poisson point processes
3.		Summary statistics
4.		Cox processes
5.		Cluster point processes
6.		Hard-core point processes
7.		Point processes given by a density
8.		Markov point processes
9.		Gibbs processes
10.		MCMC simulations
11.		Simulation-based inference
12.		Maximum likelihood for point processes
13.		Pseudo likelihood
14.		Takacs-Fiksel method

Literature:

1.		Moeller J., Waagepetersen R.P. (2004): Statistical inference and simulations for spatial point processes. Chapman and Hall/CRC, Boca Raton.
2.		Stoyan D., Kendall W.S., Mecke J. (1995): Stochastic Geometry and Its Applications. Wiley, Chichester.

Requirements:

Subject is included into these academic programs:

Program

Branch

Role

Recommended semester

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Page updated 28.4.2024 17:51:20, semester: Z/2024-5, Z,L/2023-4, Send comments about the content to the Administrators of the Academic Programs

Proposal and Realization: I. Halaška (K336), J. Novák (K336)