The spring semester 2021 will generally take place online. New presence elements as of April 26 will be communicated by the lecturers.

401-6624-11L  Applied Time Series Analysis

SemesterSpring Semester 2016
LecturersM. Dettling
Periodicityyearly recurring course
Language of instructionEnglish


AbstractThe 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.
ObjectiveGetting 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.
ContentThe 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.
Lecture notesA script will be available.
Prerequisites / NoticeThe 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.