PřF:M0130 Seminar of Random Processes - Course Information
M0130 Seminar of Random Processes
Faculty of ScienceSpring 2010
- Extent and Intensity
- 0/3/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: z (credit).
- Teacher(s)
- RNDr. Marie Forbelská, Ph.D. (lecturer)
- Guaranteed by
- prof. RNDr. Ivanka Horová, CSc.
Department of Mathematics and Statistics – Departments – Faculty of Science - Timetable of Seminar Groups
- M0130/01: Fri 11:00–13:50 MP1,01014, M. Forbelská
M0130/02: Tue 8:00–10:50 MP1,01014, M. Forbelská - Prerequisites
- NOW( M0122 Random Processes II )
Basics of the theory of probability, mathematical statistics, theory of estimation and the testing of hypothesis, elements of regression and correlation analysis. Computer skill: working knowledge of the numerical computing environment MATLAB. - 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
- Mathematics - Economics (programme PřF, M-AM)
- Mathematics (programme PřF, M-MA, specialization Applied Mathematics)
- Mathematics (programme PřF, N-MA, specialization Applied Mathematics)
- Course objectives
- Seminar is located in a computer lab and use MATLAB computing environment allowing the students to get the basic practical skill. They can run demo scripts related to individual topics of the lectures as well as fit models to simulated and real data using a variety of universal procedures. The implemented algorithms are fully transparent to the students and yield unlimited opportunity for their creativity.
- Syllabus
- Regression techniques for time series data. Box-Cox transformation. Moving average and exponential smoothing. Classical decomposition methods using additive and multiplicative models. Description and summary of serial independence using autocorrelation functions. Simulation of properties of MA(q), AR(p), ARIMA(p,d,q) processes.
- Literature
- BROCKWELL, Peter J. and Richard A. DAVIS. Introduction to time series and forecasting. 2nd ed. New York: Springer, 2002, xiv, 434. ISBN 0387953515. info
- HAMILTON, James Douglas. Time series analysis. Princeton, N.J.: Princeton University Press, 1994, xiv, 799 s. ISBN 0-691-04289-6. info
- CIPRA, Tomáš. Analýza časových řad s aplikacemi v ekonomii. 1. vyd. Praha: Alfa, Státní nakladatelství technické literatury, 1986, 246 s., ob. info
- ANDĚL, Jiří. Statistická analýza časových řad. Praha: SNTL, 1976. info
- Teaching methods
- Exercises: solving problems for understanding of basic concepts and theorems, contains also more complex problems.
- Assessment methods
- Individual project.
- Language of instruction
- Czech
- Further Comments
- The course is taught annually.
- Enrolment Statistics (Spring 2010, recent)
- Permalink: https://is.muni.cz/course/sci/spring2010/M0130