Title
Classical and objective Bayesian estimation and confidence intervals of an asymmetric loss based capability index Cpmk '
Abstract
In this paper, we introduce a new process capability index, Cpmk ' based on an asymmetric loss function (linear exponential) for normal process. To estimate Cpmk ', we first obtain eight different classical methods of estimation and then consider objective Bayesian methods of estimation under the squared error loss function and the linear exponential loss function. Extensive simulations are carried out to investigate the performance of these estimation methods in terms of the mean squared errors. In addition, we compare the performance of four bootstrap confidence intervals and the highest posterior density interval of Cpmk ' in terms of average width and coverage probability. Finally, three real-data applications from electronic industries are provided for illustrative purposes.
Year
DOI
Venue
2022
10.1002/qre.3042
QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL
Keywords
DocType
Volume
bootstrap confidence intervals, Gibbs sampling, Jeffreys prior, Monte Carlo simulation, normal distribution
Journal
38
Issue
ISSN
Citations 
4
0748-8017
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Sanku Dey112.76
Mahendra Saha200.34
Shen Zhang300.34
Min Wang47627.77