Local linear estimation of the regression function for twice censored data

Ouafae Benrabah, Feriel Bouhadjera and Elias Ould Saïd ()
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Ouafae Benrabah: Université du Littoral Cote d’Opale (ULCO), Laboratoire de Mathématiques pures et appliquées (LMPA)
Feriel Bouhadjera: Université du Littoral Cote d’Opale (ULCO), Laboratoire de Mathématiques pures et appliquées (LMPA)
Elias Ould Saïd: Université du Littoral Cote d’Opale (ULCO), Laboratoire de Mathématiques pures et appliquées (LMPA)

Statistical Papers, 2022, vol. 63, issue 2, No 7, 489-514

Abstract: 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.

Keywords: Local Linear estimation; Regression function; Survival analysis; Twice censored data; Uniform almost sure consistency; 62G05; 62G08; 62G20; 62N01; 62N02 (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s00362-021-01240-5

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