Bayesian non-parametric simulation of hazard functions

Dmitriy Belyi*, Elmira Popova, David Morton, Paul Damien

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

In Bayesian non-parametric statistics, the extended gamma process can be used to model the class of monotonic hazard functions. However, numerical evaluations of the posterior process are very difficult to compute for realistic sample sizes. To overcome this, we use Monte Carlo methods introduced by Laud, Smith, and Damien (1996) to simulate from the posterior process. We show how these methods can be used to approximate the increasing failure rate of an item, given observed failures and censored times. We then use the results to compute the optimal maintenance schedule under a specified maintenance policy.

Original languageEnglish (US)
Title of host publicationProceedings of the 2009 Winter Simulation Conference, WSC 2009
Pages475-482
Number of pages8
DOIs
StatePublished - Dec 1 2009
Event2009 Winter Simulation Conference, WSC 2009 - Austin, TX, United States
Duration: Dec 13 2009Dec 16 2009

Other

Other2009 Winter Simulation Conference, WSC 2009
CountryUnited States
CityAustin, TX
Period12/13/0912/16/09

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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