Course

Time series analysis and forecasting

Modern methods for time series analysis, modelling and forecasting (with R)

In analyzing time series one searches for structures and patterns to describe and explain the underlying process. But also for ways to use adequate models fitted to predict future values or to study the effects of alternative scenarios.

Time series occur in a wide range of disciplines, from business, economic and social sciences to biomedical and engineering contexts. This course  treats actual methods for time series analysis, modelling and forecasting.

Apart from the traditional methods for trend and seasonal decomposition of time series, more advanced statistical techniques, both in the time-domain and in the frequency domain are discussed and underlying principles are explained.

Insight in and practice with time series

In this course:

  • You gain insight in current approaches for time series analysis, modelling and forecasting, specifically:
    • Exponential Smoothing models (Simple, Holt, Holt-Winter)
    • Box-Jenkins models (ARMA, ARIMA, SARIMA)
    • Multivariate time series modesl for correlated series (dynamic regression and VARMA models)
  • You learn to analyze, to model and to validate time series data using relevant statistical software such as R, Minitab or JMP
  • You learn to use the models obtained for time series analysis forecasting and scenario analysis

Intended for

Academics and professionals who have to analyze and predict time series data in their work. The course is also suited for lecturers at universities or colleges of higher education who want to be informed on actual methods for time series analysis.

Knowledge of basic statistical techniques like testing, estimating and regression modelling is assumed.

In consultation with the participants this course can be taught in Dutch or English.

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  • Information
    Trainer: Dhr. Dr. J.J.M. Rijpkema (Eindhoven University of Technology (TU/e))
    Course data: March 18 and 25, April 1 - 2019
    Location: Campus Eindhoven University of Technology
    Price: € 1,890.00 ex. vat
    In cooperation with: TU/e, department of Mathematics & Computer Science
    Language
    The program can be taught in English on request.
  • Program

    The following topics will be treated:

    • Introduction and overview
    • Exploratory data analysis of time series
    • Models for trend and seasonal decomposition
    • Exponential Smoothing models
    • Box-Jenkins ARMA, ARIMA and SARIMA models
    • Analysis in the frequency domain: Spectral analysis and Periodogram
    • Model selection, validation and evaluation
    • Forecasting (both without and with predictor variables) and scenario analysis
    • Interpretation and presentation of the results
  • Reviews
    This course is assessed with a 8.2
    “Deep dive into applied statistics in time series forecasting.”
    Stefan Manders (ING Bank)
    “Intensive course, with practical insight into the theory of time series.”
    employee Coƶperatie VGZ
    “The course content is presented clearly and the many methods have been structured.”
    employee Belastingdienst Utrecht
    “This course is informative in many ways. The theoretical part is intensive. ”
    employee Achmea Expertise
    “Informative course, I want to frequently apply this in my daily work.”
    employee NV Nederlandse Gasunie