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TEST

, Volume 26, Issue 2, pp 353–376 | Cite as

Nonparametric latency estimation for mixture cure models

  • Ana López-ChedaEmail author
  • M. Amalia Jácome
  • Ricardo Cao
Original Paper

Abstract

A nonparametric latency estimator for mixture cure models is studied in this paper. An i.i.d. representation is obtained, the asymptotic mean squared error of the latency estimator is found, and its asymptotic normality is proven. A bootstrap bandwidth selection method is introduced and its efficiency is evaluated in a simulation study. The proposed methods are applied to a dataset of colorectal cancer patients in the University Hospital of A Coruña (CHUAC).

Keywords

Bandwidth selection Bootstrap Censored data Kernel estimation Survival analysis 

Mathematics Subject Classification

62N01 Censored data models (Survival analysis and censored data) 62N02 Estimation (Survival analysis and censored data) 62G08 Nonparametric regression (Nonparametric inference) 

Notes

Acknowledgements

The first author’s research was sponsored by the Spanish FPU (Formación de Profesorado Universitario) Grant from MECD (Ministerio de Educación, Cultura y Deporte) with reference FPU13/01371. All the authors acknowledge partial support by the MINECO (Ministerio de Economía y Competitividad) grant MTM2014-52876-R (EU ERDF support included), the MICINN (Ministerio de Ciencia e Innovación) Grant MTM2011-22392 (EU ERDF support included) and Xunta de Galicia GRC Grant CN2012/130. The authors are grateful to Dr. Sonia Pértega and Dr. Salvador Pita, at the University Hospital of A Coruña, for providing the colorectal cancer data set.

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Copyright information

© Sociedad de Estadística e Investigación Operativa 2016

Authors and Affiliations

  1. 1.Grupo MODES, INIBIC, CITIC, Departamento de Matemáticas, Facultade de InformáticaUniversidade da CoruñaCoruñaSpain
  2. 2.Grupo MODES, INIBIC, CITIC, Departamento de Matemáticas, Facultade de CienciasUniversidade da CoruñaCoruñaSpain

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