Bi6446 Time Series Forecasting

Faculty of Science
autumn 2021
Extent and Intensity
2/1/0. 3 credit(s) (plus extra credits for completion). Type of Completion: zk (examination).
Teacher(s)
prof. Ing. Jiří Holčík, CSc. (lecturer)
Guaranteed by
prof. Ing. Jiří Holčík, CSc.
RECETOX – Faculty of Science
Contact Person: prof. Ing. Jiří Holčík, CSc.
Supplier department: RECETOX – Faculty of Science
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
Course objectives
At the end of the course, students should be able to:
- know fundamental theoretical and methodological principles of methods of time series prediction not only with emphasis to biological data processing
- explain consequences and relationships between characteristics of real processes and data and applied methods and algorithms;
- apply different practical approaches to data processing to obtain required analytic results;
- design modified algorithms to process data of given particular characteristics
Learning outcomes
At the end of the course, students should be able to:
- know fundamental theoretical and methodological principles of methods of time series spectral analysis with emphasis to biological data processing
- explain consequences and relationships between characteristics of real processes and data and applied methods and algorithms;
- apply different practical approaches to data processing to obtain required analytic results;
- design modified algorithms to process data of given particular characteristics.
Syllabus
  • 1. Why prediction usually fails.
  • 2. Prediction – what is it?, preliminary analysis, transformation & adjustments, prediction models - method of simple forecasting.
  • 3. Prediction models – regression, linear prediction (autoregressive models, moving average models).
  • 4. Prediction models – linear prediction (exponential smoothing).
  • 5. Judgemental forecasting.
  • 6. Forecasting evaluation
Teaching methods
Lectures supported by Power Point presentations. Understanding of principles, methods and algorithms is emphasized. Students are continuously encouraged to be in an interaction with a lecturer.
Assessment methods
oral examination
Language of instruction
Czech
Further comments (probably available only in Czech)
The course is taught annually.
General note: Vhodné je mít základy metod zpracování signálů a spektrální analýzy.
The course is also listed under the following terms Autumn 2010 - only for the accreditation, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2011 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020, Spring 2021, Spring 2022.
  • Enrolment Statistics (autumn 2021, recent)
  • Permalink: https://is.muni.cz/course/sci/autumn2021/Bi6446