ePrints@IIScePrints@IISc Home | About | Browse | Latest Additions | Advanced Search | Contact | Help

Bayesian Analysis of Masked Series System Lifetime Data

Mukhopadhyay, Chiranjit and Basu, Sanjib (2007) Bayesian Analysis of Masked Series System Lifetime Data. In: Communications in Statistics - Theory and Methods, 36 (2). pp. 329-348.

Full text not available from this repository. (Request a copy)

Abstract

The problem of analyzing series system lifetime data with masked or partial information on cause of failure is recent, compared to that of the standard competing risks model. A generic Gibbs sampling scheme is developed in this article towards a Bayesian analysis for a general parametric competing risks model with masked cause of failure data. The masking probabilities are not subjected to the symmetry assumption and independent Dirichlet priors are used to marginalize these nuisance parameters. The developed methodology is illustrated for the case where the components of a series system have independent log-Normal life distributions by employing independent Normal-Gamma priors for these component lifetime parameters. The Gibbs sampling scheme developed for the required analysis can also be used to provide a Bayesian analysis of data arising from the conventional competing risks model of independent log-Normals, which interestingly has so far remained by and large neglected in the literature. The developed methodology is deployed to analyze a masked lifetime data of PS/2 computer systems.

Item Type: Journal Article
Additional Information: Copyright of this article belongs to Taylor and Francis.
Keywords: Censoring;Competing risks;Dirichlet distribution;Gibbs sampling;log-Normal distribution;Masking probabilities;Normal-gamma prior;Reliability.
Department/Centre: Division of Information Sciences > Management Studies
Date Deposited: 25 Jul 2008
Last Modified: 27 Aug 2008 13:38
URI: http://eprints.iisc.ernet.in/id/eprint/15269

Actions (login required)

View Item View Item