Inference Based on Incomplete Data

Eswar G. Phadia
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Eswar G. Phadia: William Paterson University of New Jersey, Department of Mathematics

Chapter Chapter 3 in Prior Processes and Their Applications, 2013, pp 155-190 from Springer

Abstract: Abstract In Chap. 2 , the applications were based on samples with complete data. In contrast, this chapter is devoted to presenting inferential procedures based on (mostly right) censored data. Heavy emphasis is given to the estimation of survival function since it plays an important role in the survival data analysis. Estimation procedures based on different priors and under various sampling schemes are discussed. Estimation of hazard rates and cumulative hazard functions is also included. This is followed by other examples which include estimation procedures in certain stochastic process models, Markov Chains, and competing risks models. Finally, estimation of the survival function in presence of covariates is presented.

Keywords: Posterior Distribution; Survival Function; Moment Generate Function; Dirichlet Process; Compete Risk Model (search for similar items in EconPapers)
Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-39280-1_3

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DOI: 10.1007/978-3-642-39280-1_3

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