Suchergebnis: Katalogdaten im Frühjahrssemester 2019

Statistik Master Information
Die hier aufgelisteten Lehrveranstaltungen gehören zum Curriculum des Master-Studiengangs Statistik. Die entsprechenden KP gelten nicht als Mobilitäts-KP, auch wenn gewisse Lerneinheiten nicht an der ETH Zürich belegt werden können.
Kernfächer
In der Regel werden die Kernfächer in jedem Themenbereich sowohl in einer mathematisch ausgerichteten als auch in einer anwendungsorientierten Art angeboten. Pro Themenbereich wird jeweils nur eine dieser beiden Arten für das Master-Diplom angerechnet.
Zeitreihen und stochastische Prozesse
NummerTitelTypECTSUmfangDozierende
401-6624-11LApplied Time SeriesW5 KP2V + 1UM. Dettling
KurzbeschreibungThe course starts with an introduction to time series analysis (examples, goal, mathematical notation). In the following, descriptive techniques, modeling and prediction as well as advanced topics will be covered.
LernzielGetting to know the mathematical properties of time series, as well as the requirements, descriptive techniques, models, advanced methods and software that are necessary such that the student can independently run an applied time series analysis.
InhaltThe course starts with an introduction to time series analysis that comprises of examples and goals. We continue with notation and descriptive analysis of time series. A major part of the course will be dedicated to modeling and forecasting of time series using the flexible class of ARMA models. More advanced topics that will be covered in the following are time series regression, state space models and spectral analysis.
SkriptA script will be available.
Voraussetzungen / BesonderesThe course starts with an introduction to time series analysis that comprises of examples and goals. We continue with notation and descriptive analysis of time series. A major part of the course will be dedicated to modeling and forecasting of time series using the flexible class of ARMA models. More advanced topics that will be covered in the following are time series regression, state space models and spectral analysis.
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