Course Details
Time series analysis
Academic Year 2024/25
DA65 course is part of 7 study plans
D-K-C-SI (N) / VHS Winter Semester 2nd year
D-K-C-SI (N) / MGS Winter Semester 2nd year
D-K-C-SI (N) / PST Winter Semester 2nd year
D-K-C-SI (N) / FMI Winter Semester 2nd year
D-K-C-SI (N) / KDS Winter Semester 2nd year
D-K-C-GK / GAK Winter Semester 2nd year
D-K-E-SI (N) / PST Winter Semester 2nd year
Course Guarantor
Institute
Language of instruction
Czech
Credits
10 credits
Semester
winter
Forms and criteria of assessment
examination
Offered to foreign students
Not to offer
Course on BUT site
Lecture
13 weeks, 3 hours/week, elective
Syllabus
1. General concepts of stochastic process. Mth -order probabilty distributions of stochastic process. Characteristics of stochastic process, poin and interval estimate of these characteristics.
2. Stationary process.
3. Ergodic process.
4. Linear regression model.
5. Linear regression model.
6. Decomposition of time series. Regression approach to trend.
7. Moving average.
8. Exponential smoothing.
9. Winter´s seasonal smoothing.
10. Periodical model - spectral density and periodogram.
11. Linear process. Moving average process - MA(q).
12. Autoregressive process - AR(p).
13. Mixed autoregression - moving average process - ARMA(p,q), ARIMA(p,d,q).