Journal of Data Science logo


Login Register

  1. Home
  2. Issues
  3. Volume 18, Issue 2 (2020)
  4. Inference and Optimal Design of Accelera ...

Journal of Data Science

Submit your article Information
  • Article info
  • More
    Article info

Inference and Optimal Design of Accelerated Life Test using Geometric Process for Generalized Half-Logistic Distribution under Progressive Type-II Censoring
Volume 18, Issue 2 (2020), pp. 358–375
H. M. Aly   S. O. Bleed   H. Z. Muhammed  

Authors

 
Placeholder
https://doi.org/10.6339/JDS.202004_18(2).0008
Pub. online: 4 August 2022      Type: Research Article      Open accessOpen Access

Published
4 August 2022

Abstract

In this paper, the geometric process model is used for analyzing constant stress accelerated life testing. The generalized half logistic lifetime distribution is considered under progressive type-II censoring. Statistical inference is developed on the basis of maximum likelihood approach for estimating the unknown parameters and getting both the asymptotic and bootstrap confidence intervals. Besides, the predictive values of the reliability function under usual conditions are found. Moreover, the method of finding the optimal value of the ratio of the geometric process is presented. Finally, a simulation study is presented to illustrate the proposed procedures and to evaluate the performance of the geometric process model.

PDF XML
PDF XML

Copyright
No copyright data available.

Keywords
Accelerated life test Geometric process Generalized Half-Logistic distribution

Metrics
since February 2021
658

Article info
views

465

PDF
downloads

Export citation

Copy and paste formatted citation
Placeholder

Download citation in file


Share


RSS

Journal of data science

  • Online ISSN: 1683-8602
  • Print ISSN: 1680-743X

About

  • About journal

For contributors

  • Submit
  • OA Policy
  • Become a Peer-reviewer

Contact us

  • JDS@ruc.edu.cn
  • No. 59 Zhongguancun Street, Haidian District Beijing, 100872, P.R. China
Powered by PubliMill  •  Privacy policy