Abstract
The interval-censored data is that represents adjacent inspection times that surround an unknown failure time. This paper gives a review of the classical approach of the maximum likelihood estimating method to parameters of three-parameters Weibull distribution with interval-censored data. It also considers the Bayes’ estimators under asymmetric three loss functions squared error loss (SEL), linear-exponential (LINEX), and generalized entropy loss (GEL) functions. For the unknown parameters of three-parameters Weibull distributions with interval-censored data. We use Lindley’s approximation to compute the Bayes estimates. Then we will apply a Monte Carlo simulation study is carried out to compare the performances of the methods using the R programming language to compute and compare the performance of the proposed estimators. A real data application is also presented. The study observed that the Bayesian estimator under generalized entropy loss (GEL) functions is preferred over the classical maximum likelihood estimator for all parameters of scale, shape, and location.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.