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Non-Parametric Bayesian Inference for Reliability Function Elicitation

Grant number: 11/16608-2
Support type:Scholarships in Brazil - Master
Effective date (Start): March 01, 2012
Effective date (End): August 31, 2013
Field of knowledge:Physical Sciences and Mathematics - Probability and Statistics - Statistics
Principal researcher:Fernando Antonio Moala
Grantee:Débora Luzia Penha
Home Institution: Faculdade de Ciências e Tecnologia (FCT). Universidade Estadual Paulista (UNESP). Campus de Presidente Prudente. Presidente Prudente , SP, Brazil

Abstract

This project intends to make an application of Bayesian nonparametric method of elicitation of priors proposed by Oakley & O'Hagan (2007), Moala (2009) and Moala & O'Hagan (2010) to estimate the reliability function, considered completely unknown in form, based only on information supplied by the specialist. The objective is the application of Bayesian analysis and its ability to incorporate a priori knowledge on the theory of reliability, which would be extremely useful when testing time is limited to a formal procedure for obtaining results about the reliability of a product. This occurs mainly in high-reliability systems, which can not afford enough samples to meet the requirements for reliability testing. In this case the information from the expert may be more viable source of information. Thus, the development of a consistent methodology that adequately represents the information provided by specialists to get the reliability is of great importance for the application of Bayesian methods and may represent an important contribution to the theory elicitation and analysis of reliability.

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Academic Publications
(References retrieved automatically from State of São Paulo Research Institutions)
PENHA, Débora Luzia. Inferência bayesiana não-paramétrica para elicitação da função de contabilidade. 2014. Master's Dissertation - Universidade Estadual Paulista (Unesp). Faculdade de Ciências e Tecnologia. Presidente Prudente Presidente Prudente.

Please report errors in scientific publications list by writing to: cdi@fapesp.br.