IAD Index of Academic Documents
  • Home Page
  • About
    • About Izmir Academy Association
    • About IAD Index
    • IAD Team
    • IAD Logos and Links
    • Policies
    • Contact
  • Submit A Journal
  • Submit A Conference
  • Submit Paper/Book
    • Submit a Preprint
    • Submit a Book
  • Contact
  • Hacettepe Journal of Mathematics and Statistics
  • Volume:45 Issue:1
  • Inference on Pr(X > Y) Based on Record Values from the Burr Type X Distribution

Inference on Pr(X > Y) Based on Record Values from the Burr Type X Distribution

Authors : Bahman TARVİRDİZADE, Hossein Kazemzadeh Gharehchobogh HOSSEİN KAZEMZADEH GHAREHCHOBOGH
Pages : 267-278
View : 51 | Download : 8
Publication Date : 2016-02-01
Article Type : Research Paper
Abstract :Our interest is in estimating the stress-strength reliability Prinsert ignore into journalissuearticles values(X > Y ); based on lower record values when X and Y are two independent but not identically distributed Burr type X random variables. The maximum likelihood estimator, Bayes and empirical Bayes estimators using Lindleys approximations, are obtained and their properties are studied. The exact confidence interval, as well as the Bayesian credible sets are obtained. Two examples are presented in order to illustrate the inferences discussed in the previous sections. A Monte Carlo simulation study is conducted to investigate and compare the performance of different types of estimators presented in this paper and to compare them with some bootstrap intervals.
Keywords : Likelihood estimation, Bayesian estimation, Burr type X distribution, Record values, Stress strength reliability, Lindley approximation

ORIGINAL ARTICLE URL

* There may have been changes in the journal, article,conference, book, preprint etc. informations. Therefore, it would be appropriate to follow the information on the official page of the source. The information here is shared for informational purposes. IAD is not responsible for incorrect or missing information.


Index of Academic Documents
İzmir Academy Association
CopyRight © 2023-2026