Course: Time Series 2

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Course title Time Series 2
Course code KMA/CASR2
Organizational form of instruction Lecture + Exercise
Level of course Master
Year of study not specified
Semester Winter
Number of ECTS credits 5
Language of instruction Czech
Status of course Compulsory, Compulsory-optional
Form of instruction Face-to-face
Work placements This is not an internship
Recommended optional programme components None
  • Müller Ivo, RNDr. PhDr. Ph.D.
  • Fišerová Eva, doc. RNDr. Ph.D.
Course content
1 Time series and random process, classification, approaches to model building. 2 Possibilities of General Linear Model in describing a trend. 3 Moving average of a general order. 4 Double exponential smoothing, comparison with simple smoothing. 5 Seasonal models, elaboration. 6 Derivation of the Model of Hidden Periodicities; periodogram and Fisher's test. 7 Box&Jenkins' approach, basic notions. 8 Moving Average process. 9 Autoregressive process. 10 General ARMA process. 11 Identification and verification.

Learning activities and teaching methods
  • Attendace - 60 hours per semester
  • Preparation for the Course Credit - 20 hours per semester
  • Preparation for the Exam - 50 hours per semester
  • Homework for Teaching - 20 hours per semester
Learning outcomes
Applying various methods of time-series analysis, development of statistical models.
Application Applying various methods of time-series analysis, development of statistical models.
Motivation to learn

Assessment methods and criteria
Oral exam, Written exam

Credit: active participation in seminars, written test. Exam: oral.
Recommended literature
  • T. Cipra. (1986). Analýza časových řad s aplikacemi v ekonomii. SNTL, Praha.

Study plans that include the course
Faculty Study plan (Version) Branch of study Category Recommended year of study Recommended semester
Faculty of Science Applications of Mathematics in Economy (2015) Mathematics courses 1 Winter
Faculty of Science Applied Mathematics (2014) Mathematics courses 2 Winter