Dynamic Inference on Survival Functions

Dani Gamerman
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Dani Gamerman: University of Warwick, Department of Statistics

A chapter in Probability and Bayesian Statistics, 1987, pp 183-192 from Springer

Abstract: Abstract The inference of survival functions based on information from censored observations is considered. The hazard function is assumed to be piecewise constant along intervals. The parameters are updated via a Bayesian conjugate analysis and information is passed through intervals via dynamic relations of the parameters. Inference is then made for the survival function of an individual (from the same population) conditioned on the observed data. Comparison with the product limit estimator, tools to criticise a model and some numerical examples are also provided.

Keywords: Hazard Function; Survival Function; Failure Time; Marginal Likelihood; Dirichlet Process (search for similar items in EconPapers)
Date: 1987
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4613-1885-9_19

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DOI: 10.1007/978-1-4613-1885-9_19

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