The Reliability Inference for Multicomponent Stress–Strength Model under the Burr X Distribution

Author:

Lio Yuhlong1ORCID,Chen Ding-Geng23ORCID,Tsai Tzong-Ru4ORCID,Wang Liang5ORCID

Affiliation:

1. Department of Mathematical Sciences, University of South Dakota, Vermillion, SD 57069, USA

2. College of Health Solutions, Arizona State University, Phoenix, AZ 85004, USA

3. Department of Statistics, University of Pretoria, Pretoria 0028, South Africa

4. Department of Statistics, Tamkang University, Tamsui District, New Taipei City 251301, Taiwan

5. School of Mathematics, Yunnan Normal University, Kunming 650500, China

Abstract

The reliability of the multicomponent stress–strength system was investigated under the two-parameter Burr X distribution model. Based on the structure of the system, the type II censored sample of strength and random sample of stress were obtained for the study. The maximum likelihood estimators were established by utilizing the type II censored Burr X distributed strength and complete random stress data sets collected from the multicomponent system. Two related approximate confidence intervals were achieved by utilizing the delta method under the asymptotic normal distribution theory and parametric bootstrap procedure. Meanwhile, point and confidence interval estimators based on alternative generalized pivotal quantities were derived. Furthermore, a likelihood ratio test to infer the equality of both scalar parameters is provided. Finally, a practical example is provided for illustration.

Funder

National Science and Technology Council, Taiwan

National Natural Science Foundation of China

Yunnan Fundamental Research Projects

Yunnan Key Laboratory of Modern Analytical Mathematics and Applications

South Africa DST-NRF-SAMRC SARChI Research

Publisher

MDPI AG

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