Classical and Bayesian estimation of the reliability function for the inverse Lindley distribution based on lower record statistics

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

Etemad Golestani Bahareh; Ormoz Ehsan; MirMostafaee ‎Seyed Mohammad Taghi Kamel

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: JOURNAL OF STATISTICAL MODELLING: THEORY AND APPLICATIONS Year:2023 | Volume:4 | Issue:2 Page(s): 183-198

Download Full-Text

View:

Download:

Cites:

Information Journal Paper

Title

Classical and Bayesian estimation of the reliability function for the inverse Lindley distribution based on lower record statistics

Author(s)

Etemad Golestani Bahareh | Ormoz Ehsan | MirMostafaee ‎Seyed Mohammad Taghi Kamel | Issue Writer Certificate

Keywords

Delta method

Importance sampling technique

Inverse Lindley distribution

Metropolis-Hastings algorithm

Survival function

Abstract

The reliability function‎, ‎or the Survival function at a specified time t‎, ‎denotes the proportion of products that remain operational beyond time t and continue to function‎. ‎This interpretation underscores the pivotal role of the Survival function and its estimation in understanding lifetime phenomena‎. ‎This paper explores the estimation of the Survival function for the Inverse Lindley distribution based on lower records‎. ‎The estimation techniques encompass maximum likelihood and bootstrap methods‎. ‎Furthermore‎, ‎Bayesian approaches employing Metropolis-Hastings and importance sampling algorithms are employed‎. ‎In addition to deriving approximate confidence intervals using the Delta method and percentile bootstrap intervals for the Survival function‎, ‎Chen and Shao's shortest width credible intervals are also determined‎. ‎A comprehensive simulation study is presented to assess the effectiveness of both point and interval estimators‎. Finally‎, ‎an application of the results is given to a real data set.

Multimedia

No record.

Cites

No record.

References

No record.

Cite

Related Journal Papers

No record.

Related Seminar Papers

No record.

Related Plans