26. Stochastic Methods in Fuzzy Time Series Analysis

  1. Reinhard Viertl

Published Online: 5 JAN 2011

DOI: 10.1002/9780470974414.ch26

Statistical Methods for Fuzzy Data

Statistical Methods for Fuzzy Data

How to Cite

Viertl, R. (2011) Stochastic Methods in Fuzzy Time Series Analysis, in Statistical Methods for Fuzzy Data, John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9780470974414.ch26

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

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Keywords:

  • stochastic methods - in fuzzy time series analysis;
  • fuzzy time series, analyzed without assumptions on stochastic model;
  • fuzzy observations, realizations of stochastic process - elements, fuzzy stochastic quantities;
  • linear approximation and prediction;
  • quality of approximation - determined by expectation of squared distance, between approximated and observed values;
  • problem, a minimization problem of a quadratic form;
  • positive semi-definiteness - of corresponding matrix;
  • minimization - a minimization of quadratic form;
  • real valued observations;
  • Kalman filtering – and remarks concerning it

Summary

This chapter contains sections titled:

  • Linear approximation and prediction

  • Remarks concerning Kalman filtering