Applying REC analysis to ensembles of sigma-point kalman filters

Authors:
Aloísio Carlos de Pina;Gerson Zaverucha
Affiliations:
Department of Systems Engineering and Computer Science, Federal University of Rio de Janeiro, COPPE/PESC, Rio de Janeiro, RJ, Brazil;Department of Systems Engineering and Computer Science, Federal University of Rio de Janeiro, COPPE/PESC, Rio de Janeiro, RJ, Brazil
Venue:
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Year:
2006

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Abstract

The Sigma-Point Kalman Filters (SPKF) is a family of filters that achieve very good performance when applied to time series. Currently most researches involving time series forecasting use the Sigma-Point Kalman Filters, however they do not use an ensemble of them, which could achieve a better performance. The REC analysis is a powerful technique for visualization and comparison of regression models. The objective of this work is to advocate the use of REC curves in order to compare the SPKF and ensembles of them and select the best model to be used.