Course Details
Time series analysis
Academic Year 2024/25
DAB032 course is part of 24 study plans
DKA-E Winter Semester 2nd year
DKA-GK Winter Semester 2nd year
DKA-K Winter Semester 2nd year
DKA-M Winter Semester 2nd year
DKA-S Winter Semester 2nd year
DKA-V Winter Semester 2nd year
DPA-E Winter Semester 2nd year
DPA-GK Winter Semester 2nd year
DPA-K Winter Semester 2nd year
DPA-M Winter Semester 2nd year
DPA-S Winter Semester 2nd year
DPA-V Winter Semester 2nd year
DKC-E Winter Semester 2nd year
DKC-GK Winter Semester 2nd year
DKC-K Winter Semester 2nd year
DKC-M Winter Semester 2nd year
DKC-S Winter Semester 2nd year
DKC-V Winter Semester 2nd year
DPC-E Winter Semester 2nd year
DPC-GK Winter Semester 2nd year
DPC-K Winter Semester 2nd year
DPC-M Winter Semester 2nd year
DPC-S Winter Semester 2nd year
DPC-V Winter Semester 2nd year
Course Guarantor
Institute
Language of instruction
Czech
Credits
10 credits
Semester
Forms and criteria of assessment
Offered to foreign students
Course on BUT site
Lecture
13 weeks, 3 hours/week, elective
Syllabus
- General concepts of stochastic process. Mth -order probabilty distributions of stochastic process. Characteristics of stochastic process, poin and interval estimate of these characteristics.
- Stationary process.
- Ergodic process.
- Linear regression model.
- Linear regression model.
- Decomposition of time series. Regression approach to trend.
- Moving average.
- Exponential smoothing.
- Winter´s seasonal smoothing.
- Periodical model – spectral density and periodogram.
- Linear process. Moving average process – MA(q).
- Autoregressive process – AR(p).
- Mixed autoregression – moving average process - ARMA(p,q), ARIMA(p,d,q).