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Graphical identification of TAR models

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2009-12
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Abstract
This paper proposes an automatic procedure to identify Threshold Autoregressive models and specify the threshold values. The proposed procedure is based on recursive estimation of arranged autoregression. The main advantage of the proposed procedure over its competitors is that the threshold values are automatically detected. The performance of the proposed procedure is evaluated using simulations and real data.
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Nonlinear time series, Recursive estimation, Arranged autoregression, TAR models, Nonlinearity test
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