The focus lies on correctly applying time series methodology on real world data for gaining new insight. Technical details and mathematical concepts will be covered on a basic level that is accessible to the heterogeneous audience consisting of students from bachelor, master and doctoral programs of various faculties.
February, 7th, 2017
Beginning of lecture: Monday, 20.02.2017. (Exercises start on 20.02.2017 at 15:15 in room HG E 1.2, with a special introduction to the "R" software)
The course organisation can be found
The script can be found
The slides can be found
Exercise classes are every two weeks starting on 20.02.2017. The first exercise class will feature an R tutorial. Please install R and RStudio and bring your laptop to the exercise classes, if possible.
Series and solutions
|Exercises||Solutions||Exercise class / Due date (Hand in Room J 68)|
|Series 1 (Time series in R)||Solutions 1||20.2.17 / 27.2.17|
|Series 2 (Decomposition, Autocorrelation)||Solutions 2||06.3.17 / 13.3.17|
|Series 3 (AR Models and Applications)||Solutions 3||20.3.17 / 27.3.17|
|Series 4 (ARMA; Time Series Regression)||Solutions 4||03.4.17 / 10.4.17|
|Series 5 (Forecasting with Time Series)||Solutions 5||08.5.17 / 15.5.17|
|Series 6 (Multivariate, Spectral Analysis)||Solutions 6||22.5.17 / 29.5.17|