Liu-type estimator in semiparametric partially linear additive models
Chuanhua Wei and
Xiaonan Wang
Journal of Nonparametric Statistics, 2016, vol. 28, issue 3, 459-468
Abstract:
Partially linear additive model is useful in statistical modelling as a multivariate nonparametric fitting technique. This paper considers statistical inference for the semiparametric model in the presence of multicollinearity. Based on the profile least-squares (PL) approach and Liu estimation method, we propose a PL Liu estimator for the parametric component. When some additional linear restrictions on the parametric component are available, the corresponding restricted Liu estimator for the parametric component is constructed. The properties of the proposed estimators are derived. Some simulations are conducted to assess the performance of the proposed procedures and the results are satisfactory. Finally, a real data example is analysed.
Date: 2016
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Persistent link: https://EconPapers.repec.org/RePEc:taf:gnstxx:v:28:y:2016:i:3:p:459-468
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DOI: 10.1080/10485252.2016.1163357
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