Semiparametric non-linear time series model selection

@inproceedings{Gao2004SemiparametricNT,
  title={Semiparametric non-linear time series model selection},
  author={Jiti Gao and Howell Tong},
  year={2004}
}
Semiparametric time series regression is often used without checking its suitability, resulting in an unnecessarily complicated model. In practice, one may encounter computational difficulties caused by the curse of dimensionality. The paper suggests that to provide more precise predictions we need to choose the most significant regressors for both the parametric and the nonparametric time series components. We develop a novel cross-validation-based model selection procedure for the… CONTINUE READING

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