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Time Series Modeling and Computation

Time series data arise in diverse applications and their modeling poses several challenges to the data analyst. This track is concerned with the use of time series models and the associated computational methods for estimating them and assessing their fit. Special attention will be given to more recently proposed methods and models whose development made possible to attack data structures that cannot be modeled by standard methodology. Examples can arise from finance, marketing, medicine, meteorology etc. Both time and spectral domain methods can be presented.

Roland Fried, TU Dormund, Germany.
Konstantinos Fokianos, University of Cyprus, Cyprus.
Andres M. Alonso, University Carlos III de Madrid, Spain.
Organized Sessions associated with this Track
  • ES03: Resampling procedures for dependent data
    Organizers: Andres M. Alonso
  • ES29: Modeling and forecasting in power markets
    Organizers: Carolina Garcia-Martos
  • ES94: Outliers and structural changes in time series
    Organizers: Roland Fried
  • ES30: Advances in dynamic modelling and computational inference
    Organizers: Richard Gerlach
  • ES66: Time series analysis
    Organizers: Cira Perna