On adaptive progressive hybrid censored Burr type III distribution: application to the nano droplet dispersion data. Issue 2 (4th March 2021)

• Record Type: Journal Article
• Authors: Panahi, Hanieh; Asadi, Saeid
• Is Part Of: Quality technology & quantitative management. Volume 18:Issue 2(2021)
• Page Start: 179
• Page End: 201
• Publication Date: 2021-03-04
• Subjects: Adaptive Type II progressive hybrid censoring -- Burr type III -- interval estimation -- likelihood inference -- metropolis-hastings algorithm -- nano droplet dispersion; Quality control -- Periodicals; Quality control -- Statistical methods -- Periodicals; Industrial management -- Periodicals; Industrial management; Management -- Research -- Methodology -- Periodicals; Qualitative research -- Periodicals; Management; Quality control; Quality control -- Statistical methods; Periodicals; 658.00721
• DOI: 10.1080/16843703.2020.1806431
• Languages: English
• ISSNs: 1684-3703

Abstract

ABSTRACT: In the current paper, the maximum likelihood and Bayes estimators for the two shape parameters of the Burr Type III distribution are investigated based on adaptive Type II progressive hybrid censored data. The maximum likelihood estimators are provided for estimating the unknown parameters. The existence and uniqueness of the maximum likelihood estimation are shown using the graphical method. The Bayes estimates are obtained under two loss functions using the Lindley's method and Metropolis-Hastings sampling procedure. Further, approximate and Bayesian intervals are constructed. Monte Carlo simulation study is performed to check the accuracy of the estimates and compare the performance of the proposed confidence intervals. Also, the nano droplet data is analyzed to illustrate the application and development of the inference methods.