24. Descriptive Methods for Fuzzy Time Series

  1. Reinhard Viertl

Published Online: 5 JAN 2011

DOI: 10.1002/9780470974414.ch24

Statistical Methods for Fuzzy Data

Statistical Methods for Fuzzy Data

How to Cite

Viertl, R. (2011) Descriptive Methods for Fuzzy Time Series, in Statistical Methods for Fuzzy Data, John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9780470974414.ch24

Author Information

  1. Vienna University of Technology, Austria

Publication History

  1. Published Online: 5 JAN 2011
  2. Published Print: 11 FEB 2011

ISBN Information

Print ISBN: 9780470699454

Online ISBN: 9780470974414



  • descriptive methods - for fuzzy time series;
  • descriptive methods, of time series analysis - working without stochastic models;
  • fuzzy time series - an ordered sequence of fuzzy numbers;
  • moving averages - long time behavior of time series;
  • elimination, possible by local approximation;
  • application of extension principle - and fuzzy data;
  • moving average procedures - kind of filtering of time series;
  • filtering or filtration of time series - procedures, transforming values of a time series;
  • linear filtering, and moving averages - linear transformations of fuzzy time series;
  • difference filters


This chapter contains sections titled:

  • Moving averages

  • Filtering

    • Linear filtering

    • Nonlinear filters

  • Exponential smoothing

  • Components model

  • Difference filters

  • Generalized Holt–Winter method

  • Presentation in the frequency domain