Comparison of presmoothing methods in kernel density estimation under censoring

Computational Statistics volume 23, pages381–406(2008)Cite this article

Abstract

The behavior of the presmoothed density estimator is studied when different ways to estimate the conditional probability of uncensoring are used. The Nadaraya–Watson, local linear and local logistic approach are compared via simulations with the classical Kaplan–Meier estimator. While the local logistic presmoothing estimator presents the best performance, the relative benefits of the local linear versus the Nadaraya–Watson estimator depend very much on the shape of some underlying functions.

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Author information

Affiliations

  1. Departamento de Matemáticas, Facultad de Ciencias, Universidade da Coruña, 15071, A Coruña, Spain

    M. A. Jácome

  2. Department of Mathematics and University Center for Statistics, Katholieke Universiteit Leuven, Box 2400, Celestijnenlaan 200B, 3001, Leuven (Heverlee), Belgium

    I. Gijbels

  3. Departamento de Matemáticas, Facultad de Informática, Universidade da Coruña, 15071, A Coruña, Spain

    R. Cao

Authors
  1. M. A. Jácome
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  2. I. Gijbels
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  3. R. Cao
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Correspondence to M. A. Jácome.

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Jácome, M.A., Gijbels, I. & Cao, R. Comparison of presmoothing methods in kernel density estimation under censoring. Comput Stat 23, 381–406 (2008). https://doi.org/10.1007/s00180-007-0076-6

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Keywords

  • Censored data
  • Kaplan–Meier estimator
  • Local linear fit
  • Nadaraya–Watson smoother
  • Survival analysis