Semiparametric Regression Smoothing of Non-linear Time Series |
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Authors: | Jiti Gao |
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Institution: | Queensland University of Technology |
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Abstract: | In this paper, we consider using a semiparametric regression approach to modelling non-linear autoregressive time series. Based on a finite series approximation to non-parametric components, an adaptive selection procedure for the number of summands in the series approximation is proposed. Meanwhile, a large sample study is detailed and a small sample simulation for the Mackey–Glass system is presented to support the large sample study. |
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Keywords: | ,-mixing , non-linear time series , partly linear additive autoregressive model , semiparametric regression smoothing |
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