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Robust estimates in generalised varying-coefficient partially linear models

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  • Tao Hu
  • Hengjian Cui

Abstract

In this article, we introduce a family of robust estimates for the parametric and nonparametric components under a generalised semiparametric varying coefficient partially linear regression model, where the data are modelled by yi|(xi, zi, ui) ∼ F (·, μi) with for some known distribution function F and link function H. A class of sieve robust estimation is proposed and the asymptotic properties of the proposed estimators are discussed. Under some mild conditions, the estimators are shown to be strongly consistent; the convergence rate of the estimator for the unknown nonparametric component is obtained and the estimator for the unknown parameter is shown to be asymptotically normally distributed. Four simulation studies are conducted to examine the small-sample properties of the proposed estimates and a real data set is used to illustrate our approach.

Suggested Citation

  • Tao Hu & Hengjian Cui, 2010. "Robust estimates in generalised varying-coefficient partially linear models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(6), pages 737-754.
    • Handle: RePEc:taf:gnstxx:v:22:y:2010:i:6:p:737-754
    DOI: 10.1080/10485250903428468
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    1. Yatchew,Adonis, 2003. "Semiparametric Regression for the Applied Econometrician," Cambridge Books, Cambridge University Press, number 9780521812832, January.
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    Cited by:

    1. Francesco Bravo, 2020. "Robust estimation and inference for general varying coefficient models with missing observations," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(4), pages 966-988, December.
    2. Bravo, Francesco, 2015. "Semiparametric estimation with missing covariates," Journal of Multivariate Analysis, Elsevier, vol. 139(C), pages 329-346.

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