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Bayesian Functional Estimation of Hazard Rates for Randomly Right Censored Data Using Fourier Series Methods

In: Statistical Modeling and Analysis for Complex Data Problems

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  • Jean-François Angers
  • Brenda MacGibbon

Abstract

This paper discusses a Bayesian functional estimation method, based on Fourier series, for the estimation of the hazard rate fronm randomly right-censored data. A nonparametric approach, assuming that the hazard rate has no specific and prespecified parametric form, is used. A simulation study is also done to compare the proposed methodology with the estimators introduced in Antoniadis et al. (1999). The method is illustrated with a real data set consisting of survival data from bone marrow transplant patients.

Suggested Citation

  • Jean-François Angers & Brenda MacGibbon, 2005. "Bayesian Functional Estimation of Hazard Rates for Randomly Right Censored Data Using Fourier Series Methods," Springer Books, in: Pierre Duchesne & Bruno RÉMillard (ed.), Statistical Modeling and Analysis for Complex Data Problems, chapter 0, pages 41-57, Springer.
    • Handle: RePEc:spr:sprchp:978-0-387-24555-3_3
    DOI: 10.1007/0-387-24555-3_3
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