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Seminar - Introduction to time series in R

Introduction to time series in R (Prüfungsnummer 3061)

(Selected Topics in Quantitative methods, in English)

The meeting will take place on:

18.10.2019 13 - 16 Uhr GD 04 I. Semeniuk / K. Gaykalov
25.10.2019 13 - 16 Uhr GD 04 I. Semeniuk / K. Gaykalov
01.11.2019 13 - 16 Uhr GD 04 I. Semeniuk / K. Gaykalov

Time series is one of the most popular topics in the modern Applied Statistics. Different models were developed to describe the behavior of observations of a variable obtained in time. In this course we consider the basic models: ARMA-, GARCH-models, their effectiveness in the description of the time dependent stochastic processes, their implementation in R. The basic knowledge of these models will let a student study other existing time series models faster, understand the principles of their construction (parameter estimation, components selection) and apply them to the real data (goodness of the model, forecast). R programming language allows to make data analysis easy, fast, fun, beautiful and creative. The use of R becomes more popular because of many reasons. That is why the time series analysis in the class will be performed in R.

Next topics will be considered in the course:

  1. Examples of Time Series. Time Series Plots in History. Time Series and Stochastic Processes. Means, Variances and Covariances. Stationarity.
  2. Models for stationary time series. Auto Regressive Moving Average Processes. ARIMA models. Backshift operator. Parameter estimation. Diagnostics and forecast in R.
  3. GARCH models. Parameter estimation. Diagnostics and forecast in R.
  4. Seasonal models.
  5. Time series regression models.