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.
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Angers, JF., MacGibbon, B. (2005). Bayesian Functional Estimation of Hazard Rates for Randomly Right Censored Data Using Fourier Series Methods. In: Duchesne, P., RÉMillard, B. (eds) Statistical Modeling and Analysis for Complex Data Problems. Springer, Boston, MA. https://doi.org/10.1007/0-387-24555-3_3
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DOI: https://doi.org/10.1007/0-387-24555-3_3
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-24554-6
Online ISBN: 978-0-387-24555-3
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