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Stationary process. Continuity, derivative and integral of a process. Spectral representation. Linear process.
Ergodicity, central limit theorems. Predictions and filtrations. ARMA models and their statistical analysis.
Last update: Branda Martin, doc. RNDr., Ph.D. (10.12.2020)
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Students gain basic knowledge of the theory of stationary processes in both time and spectral domain. The aim is also to acquaint students with basic statistical properties of time series.
Last update: Zichová Jitka, RNDr., Dr. (20.05.2022)
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The subject is terminated with the course credit (zápočet) and exam.
Obtaining the course credit is a necessary condition for taking the exam.
Criteria for obtaining the course credit, common for all the groups, are the following: 1. Obtaining at least 70 % of points from regular homeworks (Moodle); 2. Sucessfully passing two tests during the course, i.e. obtaining at least 70 % of the points in each test. For each test there will be exactly one chance to retake the test {one term common for all the groups). The planned terms will be announced at the beginning of the semester in the Moodle platform.
Due to multiple activities required during the semester a retake of the credit course is excluded.
Last update: Zichová Jitka, RNDr., Dr. (20.05.2022)
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Anděl J.: Statistická analýza časových řad. SNTL, Praha 1976 Brockwell P.J., Davis R.A.: Time series: Theory and Methods, Springer-Verlag, New York, 1987 Prášková, Z.: Základy náhodných procesů II. Karolinum, 2004. Last update: Branda Martin, doc. RNDr., Ph.D. (10.12.2020)
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Lecture + exercises. Last update: Zichová Jitka, RNDr., Dr. (20.05.2022)
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The exam consists of the written (minimum score 50% is necessary to continue in) and the oral parts. The written part lasts 90 minutes and 4 exercises have to be solved in it. If the score achieved from the written part is less than 50%, the exam is graded as "fail".
The oral part of the exam covers the subject matter in accordance with the sylabus, in the extent presented at the lectures.
Last update: Zichová Jitka, RNDr., Dr. (20.05.2022)
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Stationary processes. Continuity, differentiation and integration. Spectral representation. Linear process. Ergodicity, central limit theorems. Prediction and filtration. ARMA models and their statistical analysis. Last update: Hlubinka Daniel, doc. RNDr., Ph.D. (10.12.2020)
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