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Inference Based on Incomplete Data

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Prior Processes and Their Applications

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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.

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Authors and Affiliations

  1. Department of Mathematics, William Paterson University of New Jersey, Wayne, NJ, USA

    Eswar G. Phadia

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  1. Eswar G. Phadia
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Phadia, E.G. (2013). Inference Based on Incomplete Data. In: Prior Processes and Their Applications. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39280-1_3

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