PřF:M6444 Markov stochastic models - Course Information
M6444 Stochastic models of Markov type
Faculty of ScienceSpring 2024
- Extent and Intensity
- 2/2/0. 4 credit(s) (příf plus uk k 1 zk 2 plus 1 > 4). Type of Completion: zk (examination).
- Teacher(s)
- RNDr. Marie Budíková, Dr. (lecturer)
doc. PaedDr. RNDr. Stanislav Katina, Ph.D. (assistant) - Guaranteed by
- doc. PaedDr. RNDr. Stanislav Katina, Ph.D.
Department of Mathematics and Statistics – Departments – Faculty of Science
Supplier department: Department of Mathematics and Statistics – Departments – Faculty of Science - Timetable
- Mon 19. 2. to Sun 26. 5. Thu 8:00–9:50 M5,01013
- Timetable of Seminar Groups:
- Prerequisites
- M3121 Probability and Statistics I || M4122 Probability and Statistics II
M5444 - Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- Epidemiology and modeling (programme PřF, N-MBB)
- Course objectives
- The aim of the course is to acquaint students:
with the using of simulations in the analysis of stochastic models;
with the properties of some selected probability distributions;
with important models of queuing systems;
with the properties of the Galton-Watson branching process. - Learning outcomes
- After completing this course, the students will be able to
use statistical toolbox of MATLAB to generate pseudo-random numbers from different probability distributions;
check the conformity of the empirical distribution with the theoretical distribution;
calculate the important characteristics of queuing systems;
analyze the behavior of Galton - Watson branching process. - Syllabus
- The issue of modeling, using simulations, random number generators.
- An important probability distribution, their properties, methods of verification.
- Basic concepts of queuing theory, queuing systems with unlimited and limited capacity, optimization problems in queuing systems.
- The probability generating function and its application in the analysis of Galton - Watson branching process.
- Literature
- SKALSKÁ, Hana. Stochastické modelování. Vyd. 2., rozšíř. a uprav. Hradec Králové: Gaudeamus, 2006, 162 s. ISBN 807041488X. info
- KOŘENÁŘ, Václav. Stochastické procesy. Vyd. 1. Praha: Vysoká škola ekonomická v Praze, 2002, 227 s. ISBN 8024503115. info
- MANDL, Petr. Pravděpodobnostní dynamické modely. 1. vyd. Praha: Academia, 1985, 181 s. info
- Teaching methods
- The weekly class schedule consists of 2 hour lecture and 2 hour of class exercises with MATLAB system.
- Assessment methods
- The final exam is written, with "open book" and consists of three or four examples. Examples are evaluated on a scale from 0 to 100. It is necessary to obtain at least 51%.
- Language of instruction
- Czech
- Further comments (probably available only in Czech)
- The course is taught annually.
- Teacher's information
- The lessons are usually in Czech or in English as needed, and the
relevant terminology is always given with English equivalents.
The target skills of the study include the ability to use the English language passively and actively in their own expertise and also in potential areas of application of mathematics.
Assessment in all cases may be in Czech and English, at the student's choice.
- Enrolment Statistics (Spring 2024, recent)
- Permalink: https://is.muni.cz/course/sci/spring2024/M6444