Title :
Bayes parameter estimation for the bivariate Weibull model of Marshall-Olkin for censored data [reliability theory]
Author_Institution :
Dept. of Stat., North Carolina State Univ., Raleigh, NC, USA
fDate :
12/1/1992 12:00:00 AM
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;
Journal_Title :
Reliability, IEEE Transactions on
