TY - JOUR
T1 - A New Reliability Class-Test Statistic for Life Distributions under Convolution, Mixture and Homogeneous Shock Model
T2 - Characterizations and Applications in Engineering and Medical Fields
AU - Etman, Walid B.
AU - El-Morshedy, Mahmoud
AU - Eliwa, Mohamed S.
AU - Almohaimeed, Amani
AU - EL-Sagheer, Rashad M.
N1 - Publisher Copyright:
© 2023 by the authors.
PY - 2023/4
Y1 - 2023/4
N2 - Over the past few decades, a new area of reliability known as classes of life distributions has developed as a result of the creation of metrics for evaluating the success or failure of reliability. This paper proposes a new reliability class-test statistic for life distributions. In some reliability processes, such as convolution, mixture, and homogeneous shock models, the closure characteristics of the proposed class-test statistic are investigated. To compare the proposed class-test against some competitive tests, the Weibull, linear failure rate (LFR), and Makeham distributions are evaluated. In addition, the relationship between sample size, level of confidence, and critical values is considered to assess the efficacy of the proposed class-test. Furthermore, a Monte Carlo null distribution critical points simulation and some applications of the censored and uncensored data are performed to demonstrate the validity of the proposed class-test in reliability analysis.
AB - Over the past few decades, a new area of reliability known as classes of life distributions has developed as a result of the creation of metrics for evaluating the success or failure of reliability. This paper proposes a new reliability class-test statistic for life distributions. In some reliability processes, such as convolution, mixture, and homogeneous shock models, the closure characteristics of the proposed class-test statistic are investigated. To compare the proposed class-test against some competitive tests, the Weibull, linear failure rate (LFR), and Makeham distributions are evaluated. In addition, the relationship between sample size, level of confidence, and critical values is considered to assess the efficacy of the proposed class-test. Furthermore, a Monte Carlo null distribution critical points simulation and some applications of the censored and uncensored data are performed to demonstrate the validity of the proposed class-test in reliability analysis.
KW - aging
KW - convolution
KW - COVID-19
KW - goodness-of-fit approach
KW - numerical data
KW - Poisson shock model
KW - simulation
KW - statistics
UR - http://www.scopus.com/inward/record.url?scp=85153591409&partnerID=8YFLogxK
U2 - 10.3390/axioms12040331
DO - 10.3390/axioms12040331
M3 - Article
AN - SCOPUS:85153591409
SN - 2075-1680
VL - 12
JO - Axioms
JF - Axioms
IS - 4
M1 - 331
ER -