The Inverse Weibull Distribution as a Failure Model Under Various Loss Functions and Based on Progressive First-Failure Censored Data
Document Type
Article
Publication Date
2015
Publication Title
Quality Technology and Quantitative Management
DOI
10.1080/16843703.2015.11673434
ISSN
1684-3703
Abstract
In this article we consider statistical inferences about the unknown parameters of the inverse Weibull distribution based on progressively first-failure censoring using Bayesian procedures. The Bayes estimators are obtained based on both the symmetric and asymmetric (Linex, General Entropy and Precautionary) loss functions. There are no explicit forms for the Bayes estimators; therefore, we propose the Lindley’s approximation method to compute the Bayes estimators. A comparison between these estimators and the maximum likelihood estimator (MLE) is provided by using extensive simulation and two criteria, namely, the bias and the mean squared error. It is concluded that the approximate Bayes estimators outperform the MLEs most of the time. Real life data example is provided to illustrate our proposed estimators.
Recommended Citation
Helu, Amal, Hani Samawi.
2015.
"The Inverse Weibull Distribution as a Failure Model Under Various Loss Functions and Based on Progressive First-Failure Censored Data."
Quality Technology and Quantitative Management, 12 (4): 517-535.
doi: 10.1080/16843703.2015.11673434
https://digitalcommons.georgiasouthern.edu/biostat-facpubs/113
