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Semiparametric Regression Smoothing of Non‐linear Time Series
Author(s) -
Gao Jiti
Publication year - 1998
Publication title -
scandinavian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.359
H-Index - 65
eISSN - 1467-9469
pISSN - 0303-6898
DOI - 10.1111/1467-9469.00118
Subject(s) - mathematics , autoregressive model , series (stratigraphy) , semiparametric regression , semiparametric model , parametric statistics , statistics , smoothing , linear regression , regression , econometrics , paleontology , biology
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.