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

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Title:	The Reliability Inference for Multicomponent Stress–Strength Model under the Burr X Distribution
Authors:	Tsai, Tzong-ru
Keywords:	multicomponent stress–strength model;Burr X distribution;maximum likelihood estimation;generalized pivotal estimation;asymptotic theory
Date:	2024-03-17
Issue Date:	2024-08-07 12:06:37 (UTC+8)
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.
Relation:	AppliedMath 4(1),　p.394-426
DOI:	10.3390/appliedmath4010021
Appears in Collections:	[Graduate Institute & Department of Statistics] Journal Article

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