title: Linear Bayesian inference for accelerated Weibull model.
abstract: In this paper, we present a Bayesian approach for inference from accelerated life tests when the underlying life model is Weibull. Our approach is based on the General Linear Models framework of West, Harrison and Migon (1985). We discuss inference for the model and show that computable results can be obtained using linear Bayesian methods. We illustrate the usefulness of our approach by applying it to some actual data from accelerated life tests.
authors.affiliation: Department of Operations Research, George Washington University, Washington, D.C. 20052, USA.
authors.forename: T A
authors.initials: TA
authors.lastname: Mazzuchi
authors.forename: R
authors.initials: R
authors.lastname: Soyer
authors.forename: A L
authors.initials: AL
authors.lastname: Vopatek
mesh_terms: D001499:Bayes Theorem; D003627:Data Interpretation, Statistical; D015993:Life Tables; D016014:Linear Models