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Local influence for Liu estimators in semiparametric linear models

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  • Hadi Emami

    (University of Zanjan)

Abstract

Semiparameric linear regression models are extensions of linear models to include a nonparametric function of some covariate. They have been found to be useful in data modelling. This paper provides local influence analysis to the Liu penalized least squares estimators that uses a smoothing spline as a solution to its nonparametric component. The diagnostics under the perturbations of constant variance, individual explanatory variables and assessing the influence on the selection of the Liu penalized least squares estimators parameter are derived. The diagnostics are applied to a real data set with informative results.

Suggested Citation

  • Hadi Emami, 2018. "Local influence for Liu estimators in semiparametric linear models," Statistical Papers, Springer, vol. 59(2), pages 529-544, June.
    • Handle: RePEc:spr:stpapr:v:59:y:2018:i:2:d:10.1007_s00362-016-0775-6
    DOI: 10.1007/s00362-016-0775-6
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    References listed on IDEAS

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    Cited by:

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