Properties of non-parametric Stute estimators

Didier Alain NJAMEN NJOMEN

Abstract


In this paper, we use the linear regression model for survival data, explaining that it corresponds to an accelerated time model of lifetime see as described in Kalbfleisch and Prentice [12] and Koul et al. [15]. In this context, we adapt the jumps of the KM estimator as defined in Lopez [16] to the accelerated lifetime model. The introduction of a more restrictive hypothesis allows us to establish a strong consistency property of the Stute [24] estimator obtained by minimizing the sum of the least squares. Using the asymptotic normality of the bivariate distribution estimator proposed by Stute [26] and the Slutsky theorem, we succeed in establishing the asymptotic distribution of the Stute [24]estimator.


Keywords


Censored lifetimes; Linear regression; Kaplan-Meier jump; Nonparametric estimator; Asymptotic distribution.

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DOI: 10.19139/soic.v7i2.392

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