401-4623-00L Time Series Analysis
|Periodizität||2-jährlich wiederkehrende Veranstaltung|
|Kurzbeschreibung||Statistical analysis and modeling of observations in temporal order, which exhibit dependence. Stationarity, trend estimation, seasonal decomposition, autocorrelations,|
spectral and wavelet analysis, ARIMA-, GARCH- and state space models. Implementations in the software R.
|Lernziel||Understanding of the basic models and techniques used in time series analysis and their implementation in the statistical software R.|
|Inhalt||This course deals with modeling and analysis of variables which change randomly in time. Their essential feature is the dependence between successive observations.|
Applications occur in geophysics, engineering, economics and finance. Topics covered: Stationarity, trend estimation, seasonal decomposition, autocorrelations,
spectral and wavelet analysis, ARIMA-, GARCH- and state space models. The models and techniques are illustrated using the statistical software R.
|Literatur||A list of references will be distributed during the course.|
|Voraussetzungen / Besonderes||Basic knowledge in probability and statistics|