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).