Technical University of Liberec
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for academic year 2025/2026
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Course: Mathematical Principles of Forecasting

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Course title Mathematical Principles of Forecasting
Course code KMI/D112
Organizational form of instruction Lecture
Level of course Doctoral
Year of study 1
Semester Summer
Number of ECTS credits 0
Language of instruction Czech, English
Status of course Compulsory-optional
Form of instruction Face-to-face
Work placements Course does not contain work placement
Recommended optional programme components None
Lecturer(s)
  • Militký Jiří, prof. Ing. CSc.
Course content
unspecified

Learning activities and teaching methods
Self-study (text study, reading, problematic tasks, practical tasks, experiments, research, written assignments), Independent creative and artistic activities, Individual consultation, Seminár
Learning outcomes
Forecasting is based on the formulation of probable variants of development. It is usually a combination of the current state of scientific knowledge in a given area and knowledge of the past, usually hidden in data. The application of most mathematical and statistical methods is based on the assumption that future developments are an extrapolation of current trends. The problem is that all models are approximate and all data are uncertain (limited at least by measurement errors). Forecasting approaches are then divided into data-driven and model-driven.The logical approach is the rational approach, where the goal, knowledge and time matter. Predictive models are commonly based on time series analysis, non-parametric smoothing and causal parametric models both linear and non-linear. Statistical analysis is used in all these models.

Prerequisites
unspecified

Assessment methods and criteria
Oral exam

Recommended literature
  • ABRAHAM, B., LEDOLTER, J. Statistical Methods for Forecasting. Hoboken: John Wiley & Sons, 2005. ISBN 978-04-7176-987-3.
  • BROCKWELL, P.J., DAVIS, R.A. Introduction to Time Series and Forecasting. Berlin: Springer, 2016. ISBN 978 0387953519.
  • KHARIN, Y. Robustness in Statistical Forecasting. Berlin: Springer, 2013. ISBN 978-3-319-00840-0.
  • MELOUN, M., MILITKÝ, J., HILL, M. Statistická analýza vícerozměrných dat v příkladech. Praha: Academia Praha, 2012. ISBN 978-80-2463-618-4.
  • MELOUN, M., MILITKÝ J. Interaktivní statistická analýza dat. Praha: Karolinum, 2012. ISBN 9788024621739 .
  • MELOUN, M., MILITKÝ, J. Statistical Data Analysis. Cambridge: Woodhead Publishing, 2011. ISBN 97808 57090102.
  • OVERMAN, A. R., SCHOLTZ, R.V. Mathematical Models of Crop Growth and Yield. Boca Raton: CRC Press, 2002. ISBN 978-0824708252.
  • PAN, J. X., FANG, K.T. Growth Curve Models and Statistical Diagnostics. Berlin: Springer, 2002. ISBN 978-0-387-21812-0.


Study plans that include the course
Faculty Study plan (Version) Category of Branch/Specialization Recommended year of study Recommended semester
Technical University of Liberec, date of update: 03.11.2025 23:50. Data created for academic year 2025/2026