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Asymptotic normality of a relative error functional regression estimator under left truncation and right censoring

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  • Adel Boucetta
  • Zohra Guessoum
  • Elias Ould-Said

Abstract

In this article, we introduce a non parametric regression estimator based on a relative error criterion, for left truncated and right censored data with functional predictors. Left truncation and right censoring are common forms of incomplete data in survival analysis, where the event time of interest is only observed within a certain interval which adds some challenges to the regression task. We establish the asymptotic normality of our estimator and develop a procedure for constructing confidence intervals for the predicted responses. The theoretical results obtained are supported using simulation studies and a real data example from the energy field.

Suggested Citation

  • Adel Boucetta & Zohra Guessoum & Elias Ould-Said, 2025. "Asymptotic normality of a relative error functional regression estimator under left truncation and right censoring," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 54(13), pages 4207-4230, July.
    • Handle: RePEc:taf:lstaxx:v:54:y:2025:i:13:p:4207-4230
    DOI: 10.1080/03610926.2024.2417232
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