Journal
QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL
Volume 37, Issue 5, Pages 2263-2275Publisher
WILEY
DOI: 10.1002/qre.2856
Keywords
confidence interval; generalized confidence interval; generalized pivotal quantity; inverse Gaussian distribution; stress– strength
Categories
Funding
- First Class Discipline of Zhejiang - A(Zhejiang Gongshang University -Statistics)
- National Natural Science Foundation of China [11801210, 11871431]
- Anhui Provincial Department of Education Key Fund [KJ2015A166]
- Zhejiang Provincial Natural Science Foundation of China [LY18G010003]
- Natural Science Research Project of Universities in Anhui Province [KJHS2019B06]
- Anhui Provincial Excellent Youth Talent Fund Project [gxyq2017075]
- Huangshan University Research Project [2013xkj010]
Ask authors/readers for more resources
This paper discusses interval estimation for the inverse Gaussian distribution, deriving generalized confidence intervals and prediction intervals. Through simulation, it is shown that the proposed intervals have higher coverage probabilities compared to traditional methods like Wald CIs and bootstrap-p CIs. Additionally, the proposed procedures are illustrated using two examples.
In this paper, we consider interval estimation for the inverse Gaussian (IG) distribution. Using generalized pivotal quantity method, we derive the generalized confidence intervals (GCIs) for the model parameters and some quantities such as the quantile, the reliability function of the lifetime, the failure rate function, and the mean residual lifetime. We verify that the GCI of the scale parameter is the same as its commonly used exact CI. We also obtain the generalized prediction intervals (GPIs) for future failure times based on the observed failure data set. In addition, we get the GCI for the reliability of the stress-strength model when the stress and strength variables follow the IG distributions with different parameters. We compare the proposed GCIs and GPIs with the Wald CIs and bootstrap-p CIs by simulation. The simulation results show that the proposed GCIs and GPIs are superior to the Wald CIs and the bootstrap-p CIs in terms of the coverage probability. Finally, two examples are used to illustrate the proposed procedures.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available