Optimal sequential Bayesian analysis for degradation tests.
Lifetime Data Anal
; 22(3): 405-28, 2016 07.
Article
em En
| MEDLINE
| ID: mdl-26307336
Degradation tests are especially difficult to conduct for items with high reliability. Test costs, caused mainly by prolonged item duration and item destruction costs, establish the necessity of sequential degradation test designs. We propose a methodology that sequentially selects the optimal observation times to measure the degradation, using a convenient rule that maximizes the inference precision and minimizes test costs. In particular our objective is to estimate a quantile of the time to failure distribution, where the degradation process is modelled as a linear model using Bayesian inference. The proposed sequential analysis is based on an index that measures the expected discrepancy between the estimated quantile and its corresponding prediction, using Monte Carlo methods. The procedure was successfully implemented for simulated and real data.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Modelos Lineares
/
Método de Monte Carlo
/
Teorema de Bayes
Tipo de estudo:
Health_economic_evaluation
/
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
Lifetime Data Anal
Ano de publicação:
2016
Tipo de documento:
Article
País de afiliação:
México
País de publicação:
Estados Unidos