Title

Bayesian Life Test Planning for Log-Location-Scale Family of Distributions

Campus Units

Statistics

Document Type

Article

Publication Version

Accepted Manuscript

Publication Date

2015

Journal or Book Title

Journal of Quality Technology

Volume

47

Issue

4

First Page

336

Last Page

350

DOI

10.1080/00224065.2015.11918138

Abstract

This paper describes Bayesian methods for life test planning with censored data from a log-location-scale distribution when prior information of the distribution parameters is available. We use a Bayesian criterion based on the estimation precision of a distribution quantile. A large-sample normal approximation gives a simplified, easy-to-interpret, yet valid approach to this planning problem, where in general no closed-form solutions are available. To illustrate this approach, we present numerical investigations using the Weibull distribution with type II censoring. We also assess the effects of prior distribution choice. A simulation approach of the same Bayesian problem is also presented as a tool for visualization and validation. The validation results generally are consistent with those from the large-sample approximation approach.

Comments

This is an Accepted Manuscript of an article published by Taylor & Francis as Hong, Yili, Caleb King, Yao Zhang, and William Q. Meeker. "Bayesian life test planning for log-location-scale family of distributions." Journal of Quality Technology 47, no. 4 (2015): 336-350. DOI: 10.1080/00224065.2015.11918138. Posted with permission.

Copyright Owner

Taylor & Francis

Language

en

File Format

application/pdf

Published Version

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