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Time Series Analysis

Prof. Dr.-Ing. F. Neitzel – Technische Universität Berlin


Thursday, October 1 andFriday, October 2, 2015
TU Berlin, Department for Geodesy and Geoinformation Science
Straße des 17. Juni 135, 10623 Berlin
Main Building, Room H6131

A time series is a sequence of data points, measured typically at successive points in time spaced at uniform time intervals. Examples of time series are the daily closing value of the Dow Jones Industrial Average and the annual flow volume of the Nile River at Aswan. Time series are very frequently plotted via line charts and are used in statistics, signal processing, pattern recognition, econometrics, mathematical finance, weather forecasting, earthquake prediction, electroencephalography, control engineering, astronomy, and communications engineering. Time series analysis comprises methods for analysing time series data in order to extract meaningful statistics and other characteristics of the data [Wikipedia 2014].

Day 1 - Morning Session

  • Introduction into time series analysis
  • Autocovariance / autocorrelation
  • Crosscorrelation
  • Regression Analysis

Day 1 - Afternoon Session

  • Exercises about the content of the morning session

Day 2 - Morning Session

  • Filtering
  • Fourier analysis

Day 2 - Afternoon Session

  • Exercises about the content of the morning session

The content of the lectures will be illustrated by exercises which are carried out by every student on the computer using Matlab / Octave. All required documents and data will be provided.