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Abstract. We construct a general class of non‐linear models, called ‘state‐dependent models’, which have a very flexible non‐linear structure and which contain, as special cases, bilinear, threshold autoregressive, and exponential autoregressive models. We describe a sequential type of recursive algorithm for identifying state‐dependent models, and show how such models may be used for forecasting and for indicating specific types of non‐linear behaviour.
Mark Priestley (Tue,) studied this question.
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