## Marcel Dettling: Catalogue data in Spring Semester 2020 |

Name | Dr. Marcel Dettling |

Address | ZHAW - IDP 8401 Winterthur SWITZERLAND |

Telephone | 058 934 70 23 |

marcel.dettling@math.ethz.ch | |

Department | Mathematics |

Relationship | Lecturer |

Number | Title | ECTS | Hours | Lecturers | |
---|---|---|---|---|---|

401-6624-11L | Applied Time Series | 5 credits | 2V + 1U | M. Dettling | |

Abstract | The 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. | ||||

Objective | Getting 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. | ||||

Content | The 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 notes | A script will be available. | ||||

Prerequisites / Notice | The 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. | ||||

447-6624-01L | Applied Time Series I Only for DAS and CAS in Applied Statistics. | 2 credits | 1V + 1U | M. Dettling | |

Abstract | Introduction to time series analysis: examples, goals and mathematical notation. Descriptive techniques, modelling and prediction. | ||||

Objective | Getting to know the mathematical properties of time series, as well as the requirements, descriptive techniques, models and software that are necessary such that the student can independently run an applied time series analysis. | ||||

Content | The 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. | ||||

Lecture notes | A script will be available. | ||||

447-6624-02L | Applied Time Series II Only for DAS and CAS in Applied Statistics. | 4 credits | 1V + 1U | M. Dettling | |

Abstract | More advanced topics in time series analysis like time series regression, state space models and spectral analysis. | ||||

Objective | Getting to know advanced methods and software that are necessary such that the student can independently run an applied time series analysis. | ||||

Lecture notes | A script will be available. |