PřF:M0130 Seminar of Random Precesses - Course Information
M0130 Seminar of Random Precesses
Faculty of ScienceSpring 2008
- 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 8:00–10:50 M3,04005 - dříve Janáčkovo nám. 2a, M. Forbelská
M0130/02: Mon 13:00–15:50 M3,04005 - dříve Janáčkovo nám. 2a, M. Forbelská - Prerequisites
- NOW( M0122 Random Processes II )
Algebra: matrix calculus, vector spaces. Selected topics from Mathematical Analysis: Fourier series. Probability and statistics: random variables and random vectors, their distribution, moment characteristics, independence, linear regression, hypotheses testing. 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.
- Language of instruction
- Czech
- Further Comments
- The course is taught annually.
- Enrolment Statistics (Spring 2008, recent)
- Permalink: https://is.muni.cz/course/sci/spring2008/M0130