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Generalized Type-I Hybrid Censoring Scheme in Estimation Competing Risks Chen Lifetime Populations
Author(s) -
Neveen Sayed-Ahmed,
Taghreed M. Jawa,
Tahani A. Aloafi,
F. S. Bayones,
Azhari A. Elhag,
Jamel Bouslimi,
G. A. Abd-Elmougod
Publication year - 2021
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2021/6693243
Subject(s) - censoring (clinical trials) , bayes' theorem , statistics , mathematics , inference , confidence interval , chen , statistical inference , accelerated life testing , computer science , bayesian probability , artificial intelligence , paleontology , weibull distribution , biology
Different types of censoring scheme are investigated; however, statistical inference on censoring scheme which can save the ideal test time and the minimum number of failures is needed. The generalized type-I hybrid censoring scheme (GHCS) solves this problem. Competing the risk models under the GHCS when time to failure has Chen lifetime distribution (CD) is adopted in this research with consideration of only two cases of failure. Partially step-stress accelerated life tests (ALTs) are applied to obtain enough failure times in a small period to achieve a highly reliable product. The problem of parameter estimation under maximum likelihood (ML) and Bayes methods is discussed. The asymptotic confidence interval as well as the Bayes credible interval is constructed. The validity of theoretical results is assessed and compared through simulation study. Finally, brief comments are reported to describe the behaviour of the estimation results.

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