Course detail
Time series analysis
FAST-DAB032Acad. year: 2021/2022
Stochastic processes, mth-order probabilty distributions of stochastic processes, characteristics of stochastic process, point and interval estimate of these characteristics, stationary random processes, ergodic processes.
Decomposition of time series -moving averages, exponential smoothing, Winters seasonal smoothing.
The Box-Jenkins approach (linear process, moving average process, autoregressive process, mixed autoregression-moving average process - identification of a model, estimation of parameters, verification of a model).
Spectral density and periodogram.
The use of statistical system STATISTICA and EXCEL for time analysis.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Learning outcomes of the course unit
Prerequisites
Basics of the theory of probability, mathematical statistics and linear algebra - the normal distribution law, numeric characteristics of random variables and vectors and their point and interval estimates, principles of the testing of statistical hypotheses, solving a system of linear equations, inverse to a matrix
Co-requisites
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
Course curriculum
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).
Work placements
Aims
Using statistical programs, they should be able to identify Box-Jenkins models, estimate the parameters of a model, judge the adequacy of a model and construct forecasts.
Specification of controlled education, way of implementation and compensation for absences
Recommended optional programme components
Prerequisites and corequisites
Basic literature
Recommended reading
Classification of course in study plans
- Programme DPA-M Doctoral 2 year of study, winter semester, compulsory-optional
- Programme DPC-M Doctoral 2 year of study, winter semester, compulsory-optional
- Programme DPA-K Doctoral 2 year of study, winter semester, compulsory-optional
- Programme DPC-K Doctoral 2 year of study, winter semester, compulsory-optional
- Programme DPA-V Doctoral 2 year of study, winter semester, compulsory-optional
- Programme DPC-V Doctoral 2 year of study, winter semester, compulsory-optional
- Programme DPA-S Doctoral 2 year of study, winter semester, compulsory-optional
- Programme DPC-S Doctoral 2 year of study, winter semester, compulsory-optional
- Programme DPA-E Doctoral 2 year of study, winter semester, compulsory-optional
- Programme DPC-E Doctoral 2 year of study, winter semester, compulsory-optional
- Programme DPA-GK Doctoral 2 year of study, winter semester, compulsory-optional
- Programme DPC-GK Doctoral 2 year of study, winter semester, compulsory-optional
- Programme DKA-M Doctoral 2 year of study, winter semester, compulsory-optional
- Programme DKC-M Doctoral 2 year of study, winter semester, compulsory-optional
- Programme DKA-K Doctoral 2 year of study, winter semester, compulsory-optional
- Programme DKC-K Doctoral 2 year of study, winter semester, compulsory-optional
- Programme DKA-V Doctoral 2 year of study, winter semester, compulsory-optional
- Programme DKC-V Doctoral 2 year of study, winter semester, compulsory-optional
- Programme DKA-S Doctoral 2 year of study, winter semester, compulsory-optional
- Programme DKC-S Doctoral 2 year of study, winter semester, compulsory-optional
- Programme DKA-E Doctoral 2 year of study, winter semester, compulsory-optional
- Programme DKC-E Doctoral 2 year of study, winter semester, compulsory-optional
- Programme DKA-GK Doctoral 2 year of study, winter semester, compulsory-optional
- Programme DKC-GK Doctoral 2 year of study, winter semester, compulsory-optional
Type of course unit
Lecture
Teacher / Lecturer
Syllabus