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Varying coefficient single-index regression model with missing responses under rank-based modelling

Author

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  • Masego Otlaadisa
  • Huybrechts F. Bindele
  • Asheber Abebe
  • Hannah Correia

Abstract

A varying coefficients single-index regression model with responses missing at random is considered. Rank-based estimators of the index coefficient and the functional coefficients are studied, and their asymptotic properties (consistency and asymptotic normality) are established under mild conditions. To demonstrate the performance of the proposed approach, Monte Carlo simulation experiments are carried out and show that the proposed approach provides robust and more efficient estimators compared to its least-squares counterpart. This is demonstrated under different model error structures, including the standard normal, the t and the contaminated model error distributions. Finally, a real data example is given to illustrate our proposed method.

Suggested Citation

  • Masego Otlaadisa & Huybrechts F. Bindele & Asheber Abebe & Hannah Correia, 2022. "Varying coefficient single-index regression model with missing responses under rank-based modelling," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 34(2), pages 319-343, April.
    • Handle: RePEc:taf:gnstxx:v:34:y:2022:i:2:p:319-343
    DOI: 10.1080/10485252.2022.2047677
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