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 not specified
Semester Summer
Number of ECTS credits 0
Language of instruction Czech
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
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