Nonparametric Inference for the Stress-Strength Model under Right Censoring

The stress-strength model is widely applied in reliability. Observations are often subject to right censoring due to some practical limitations. In such circumstances, the statistical inference for the stress-strength model is demanding, although lacking. We propose a nonparametric method for the in...

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Bibliographic Details
Published inWuhan University journal of natural sciences Vol. 20; no. 3; pp. 202 - 206
Main Authors Qi, Hui, Qi, Fei, Jichang, Yu
Format Journal Article
LanguageEnglish
Published Wuhan Wuhan University 01.06.2015
Subjects
Biomedical and Life Sciences
Computer Science
Life Sciences
Materials Science
Mathematics
O 213.2
right censoring
stress-strength model
reliability
Kapla-Meier estimator
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Summary:The stress-strength model is widely applied in reliability. Observations are often subject to right censoring due to some practical limitations. In such circumstances, the statistical inference for the stress-strength model is demanding, although lacking. We propose a nonparametric method for the inference of the stress-strength model when the observations are subject to right censoring. The asymptotic properties are also established. The practical utility of the proposed method is assessed through both simulated and real data sets.
Bibliography:42-1405/N
reliability right censoring Kapla-Meier estimator stress-strength model
The stress-strength model is widely applied in reliability. Observations are often subject to right censoring due to some practical limitations. In such circumstances, the statistical inference for the stress-strength model is demanding, although lacking. We propose a nonparametric method for the inference of the stress-strength model when the observations are subject to right censoring. The asymptotic properties are also established. The practical utility of the proposed method is assessed through both simulated and real data sets.
ISSN:1007-1202
1993-4998
DOI:10.1007/s11859-015-1082-0