2024-02-27T10:59:07Zhttps://docta.ucm.es/rest/oai/requestoai:docta.ucm.es:20.500.14352/719292023-08-25T16:02:48Zcom_20.500.14352_14col_20.500.14352_15
Robust inference for non-destructive one-shot device testing under step-stress model with exponential lifetimes
Balakrishnan, Narayanaswamy
Castilla González, Elena María
Jaenada Malagón, María
Pardo Llorente, Leandro
519.8
Methodology
Statistics Theory
Matemáticas (Matemáticas)
Investigación operativa (Matemáticas)
12 Matemáticas
1207 Investigación Operativa
One-shot devices analysis involves an extreme case of interval censoring, wherein one can only know whether the failure time is either before or after the test time. Some kind of one-shot devices do not get destroyed when tested, and so can continue within the experiment, providing extra information for inference, if they did not fail before an inspection time. In addition, their reliability can be rapidly estimated via accelerated life tests (ALTs) by running the tests at varying and higher stress levels than working conditions. In particular, step-stress tests allow the experimenter to increase the stress levels at pre-fixed times gradually during the life-testing experiment. The cumulative exposure model is commonly assumed for step-stress models, relating the lifetime distribution of units at one stress level to the lifetime distributions at preceding stress levels. In this paper, we develop robust estimators and Z-type test statistics based on the density power divergence (DPD) for testing linear null hypothesis for non-destructive one-shot devices under the step-stress ALTs with exponential lifetime distribution. We study asymptotic and robustness properties of the estimators and test statistics, yielding point estimation and conffidence intervals for different lifetime characteristic such as reliability, distribution quantiles and mean lifetime of the devices. A simulation study is carried out to assess the performance of the methods of inference developed here and some real-life data sets are analyzed ffinally for illustrative purpose.
Depto. de Estadística e Investigación Operativa
Fac. de Ciencias Matemáticas
FALSE
unpub
2023-06-22T10:57:04Z
2023-06-22T10:57:04Z
2022
journal article
https://hdl.handle.net/20.500.14352/71929
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eng
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