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In this paper developments in the analysis of univariate nonlinear time series are considered. First a number of commonly used nonlinear models are presented. The next section is devoted to methods of testing linearity, which is an important part of nonlinear model building. Techniques of...
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In this paper we examine the forecast accuracy of linear autoregressive, smooth transition autoregressive (STAR), and … class. The point forecast results indicate that the STAR model generally outperforms linear autoregressive models. It also … importance. The results for neural network models are mixed in the sense that at long forecast horizons, an NN model obtained …
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In this paper we propose a method for determining the number of regimes in threshold autoregressive models using smooth transition autoregression as a tool. As the smooth transition model is just an approximation to the threshold autoregressive one, no asymptotic properties are claimed for the...
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Changes in the seasonal patterns of macroeconomic time series may be due to the effects of business cycle fluctuations or to technological and institutional change or both. We examine the relative importance of these two sources of change in seasonality for quarterly industrial production series...
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