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Time Series Modeling and Forecasting Using Memetic Algorithms for Regime-Switching Models
2012
IEEE Transactions on Neural Networks and Learning Systems
In this brief, we present a novel model fitting procedure for the neuro-coefficient smooth transition autoregressive model (NCSTAR), as presented by Medeiros and Veiga. The model is endowed with a statistically founded iterative building procedure and can be interpreted in terms of fuzzy rule-based systems. The interpretability of the generated models and a mathematically sound building procedure are two very important properties of forecasting models. The model fitting procedure employed by
doi:10.1109/tnnls.2012.2216898
pmid:24808077
fatcat:k2poyuvkgzev3i3bgcvn3r3l3u