Testing for Remaining Autocorrelation of the residuals in the Framework of Fuzzy Rule-Based Time Series Modelling

@article{Aznarte2010TestingFR,
  title={Testing for Remaining Autocorrelation of the residuals in the Framework of Fuzzy Rule-Based Time Series Modelling},
  author={Jos{\'e} Luis Aznarte and Marcelo C. Medeiros and Jos{\'e} Manuel Ben{\'i}tez},
  journal={International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems},
  year={2010},
  volume={18},
  pages={371-387}
}
In time series analysis remaining autocorrelation in the errors of a model implies that it is failing to properly capture the structure of time-dependence of the series under study. This can be used as a diagnostic checking tool and as an indicator of the adequacy of the model. Through the study of the errors of the model in the Lagrange Multiplier testing framework, in this paper we derive (and validate using simulated and real world examples) a hypothesis test which allows us to determine if… CONTINUE READING

Similar Papers

References

Publications referenced by this paper.
SHOWING 1-10 OF 44 REFERENCES

a statistical approach, J

M. C. Medeiros, T. Teräsvirta, G. Rech, Building neural network models for time series
  • Forecasting 25(1)
  • 2006
VIEW 1 EXCERPT
HIGHLY INFLUENTIAL

Beńıtez, Linearity testing for fuzzy rule-based models

J.L.M. Aznarte, J.M.M.C. Medeiros
  • Fuzzy Sets and Systems, in press,
  • 2010
VIEW 2 EXCERPTS

Beńıtez, Neural-autoregressive time series models with fuzzy equivalences

J.M.J.L.M. Aznarte
  • IEEE Transactions on Neural Networks,
  • 2010
VIEW 3 EXCERPTS

Neural - autoregressive time series models with fuzzy equivalences

J. M. Beńıtez
  • IEEE Transactions on Neural Networks
  • 2010

A study of statisticial techniques and performance measures for

A. Fernández S. Garćıa, J. Luengo, F. Herrera
  • genetics - based machine learning : Accuracy and interpretability , Soft Computing
  • 2009

A study of statisticial techniques and performance measures for genetics-based machine learning: Accuracy and interpretability

S. Garćıa, A. Fernández, J. Luengo, F. Herrera
  • Soft Computing
  • 2009

Generating dynamic fuzzy models for prediction problems

  • NAFIPS 2009 - 2009 Annual Meeting of the North American Fuzzy Information Processing Society
  • 2009
VIEW 2 EXCERPTS