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Local linear estimation of the regression function for twice censored data

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Abstract

This paper is concerned with a nonparametric estimator of the regression function based on the local linear estimation method in a twice censoring setting. The proposed method avoid the problem of boundary effect and reduces the bias term. Under suitable assumptions, the strong uniform almost sure consistency with rate is established and the finite sample properties of the local linear regression smoother is investigated by means of a simulation study.

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Acknowledgements

The authors are grateful to the two anonymous referees whose remarks and criticisms allowed us to improve greatly the first version in various points, more particularly the simulation part.

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Correspondence to Elias Ould Saïd.

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Benrabah, O., Bouhadjera, F. & Ould Saïd, E. Local linear estimation of the regression function for twice censored data. Stat Papers 63, 489–514 (2022). https://doi.org/10.1007/s00362-021-01240-5

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  • DOI: https://doi.org/10.1007/s00362-021-01240-5

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