## Abstract Forecasting for nonlinear time series is an important topic in time series analysis. Existing numerical algorithms for multiβstepβahead forecasting ignore accuracy checking, alternative Monte Carlo methods are also computationally very demanding and their accuracy is difficult to contro
A network of autoregressive processing units for time series modeling
β Scribed by Mikko Lehtokangas; Jukka Saarinen; Kimmo Kaski; Pentti Huuhtanen
- Publisher
- Elsevier Science
- Year
- 1996
- Tongue
- English
- Weight
- 680 KB
- Volume
- 75
- Category
- Article
- ISSN
- 0096-3003
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