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Lecturer(s)
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Pavlů Ivana, Mgr. Ph.D.
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Vencálek Ondřej, doc. Mgr. Ph.D.
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Course content
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1 Definition, types of time series, standard characteristics. 2 Approaches to modelling, additive and multiplicative decomposition. 3 Trend in time series, constant trend, linear trend. 4 Quadratic trend, exponential trend. 5 Exponential trend and shifted exponential trend, method of chosen points. 6 Logistic trend, Gompertz curve, measures of fit. 7 Non-centered moving averages, centered moving averages. 8 Opening and ending moving averages, prediction moving averages. 9 Analysis of periodic component, model of hidden periods, periodogram, Fisher's test. 10 Description of a seasonal component, models of constant seasons. 11 Models of proportional seasons, estimating of seasonal factors. 12 Exponential smoothing. 13 Analysis of the random component, tests of randomness.
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Learning activities and teaching methods
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Lecture
- Attendace
- 39 hours per semester
- Preparation for the Course Credit
- 20 hours per semester
- Preparation for the Exam
- 50 hours per semester
- Homework for Teaching
- 10 hours per semester
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Learning outcomes
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Applying various methods of time-series analysis, development of statistical models.
Application Applying various methods of time-series analysis, development of statistical models.
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Prerequisites
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Motivation to learn
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Assessment methods and criteria
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Oral exam, Written exam
Credit: active participation in seminars, written test. Exam: oral.
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Recommended literature
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J. Seger, R. Hindls. (1995). Statistické metody v tržním hospodářství. Victoria Publishing, Praha.
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