Semiparametric regression smoothing of non-linear time series

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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.

Original languageEnglish
Pages (from-to)521-539
Number of pages19
JournalScandinavian Journal of Statistics
Issue number3
Publication statusPublished - 1 Jan 1998


  • Non-linear time series
  • Partly linear additive autoregressive model
  • Semiparametric regression smoothing
  • α-mixing

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