Bayes parameter estimation for the bivariate Weibull model of Marshall-Olkin for censored data [reliability theory]

Author

Lu, Jye-Chyi

Author_Institution

Dept. of Stat., North Carolina State Univ., Raleigh, NC, USA

Volume

41

Issue

4

fYear

1992

fDate

12/1/1992 12:00:00 AM

Firstpage

608

Lastpage

615

Abstract

Industrial applications frequently require statistical procedures to analyze life-test data from various sources, particularly in situations where observations are limited. The author develops a Bayes parameter estimation method for bivariate censored data collected from both system and component levels. The bivariate Weibull distribution of Marshall & Olkin (1967) is used to model lifetimes of components in a two-component system. Closed-form Bayes estimators of the model parameters are proposed along with their variances and high-probability density intervals

Keywords

Bayes methods; failure analysis; life testing; parameter estimation; probability; reliability theory; Bayes parameter estimation; bivariate Weibull model; censored data; component; failure analysis; life testing; lifetimes; observations; probability; reliability theory; system; Batteries; Life estimation; Life testing; Lifetime estimation; Parameter estimation; Power generation; Probability; Statistical analysis; System testing; Weibull distribution;

fLanguage

English

Journal_Title

Reliability, IEEE Transactions on

Publisher

ieee

ISSN

0018-9529

Type

jour

DOI

10.1109/24.249597

Filename

249597