2006 | OriginalPaper | Chapter
Applying REC Analysis to Ensembles of Sigma-Point Kalman Filters
Authors : Aloísio Carlos de Pina, Gerson Zaverucha
Published in: Artificial Neural Networks – ICANN 2006
Publisher: Springer Berlin Heidelberg
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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.