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Forecasting nonlinear time series with a hybrid methodology

✍ Scribed by Cagdas Hakan Aladag; Erol Egrioglu; Cem Kadilar

Book ID: 108052468
Publisher: Elsevier Science
Year: 2009
Tongue: English
Weight: 298 KB
Volume: 22
Category: Article
ISSN: 0893-9659
DOI: 10.1016/j.aml.2009.02.006

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## Abstract Forecasting for nonlinear time series is an important topic in time series analysis. Existing numerical algorithms for multi‐step‐ahead forecasting ignore accuracy checking, alternative Monte Carlo methods are also computationally very demanding and their accuracy is difficult to contro

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