On sufficient dimension reduction for proportional censorship model with covariates

نویسنده

  • Xuerong Meggie Wen
چکیده

The requirement of constant censoring parameter β in Koziol–Green (KG) model is too restrictive. When covariates are present, the conditional KG model (Veraverbekea and Cadarso-Suárez, 2000) which allows β to be dependent on the covariates is more realistic. In this paper, using sufficient dimension reduction methods, we provide a model-free diagnostic tool to test if β is a function of the covariates. Our method also allows us to conduct a model-free selection of the related covariates. A simulation study and a real data analysis are also included to illustrate our approach. © 2010 Elsevier B.V. All rights reserved.

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عنوان ژورنال:
  • Computational Statistics & Data Analysis

دوره 54  شماره 

صفحات  -

تاریخ انتشار 2010