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Robust inference for one‐shot device testing data under exponential lifetime model with multiple stresses

N. Balakrishnan, Elena Castilla, Nirian Martín, Leandro Pardo

2020Quality and Reliability Engineering International21 citationsDOIOpen Access PDF

Abstract

Abstract Introduced robust density‐based estimators in the context of one‐shot devices with exponential lifetimes under a single stress factor. However, it is usual to have several stress factors in industrial experiments involving one‐shot devices. In this paper, the weighted minimum density power divergence estimators (WMDPDEs) are developed as a natural extension of the classical maximum likelihood estimators (MLEs) for one‐shot device testing data under exponential lifetime model with multiple stresses. Based on these estimators, Wald‐type test statistics are also developed. Through a simulation study, it is shown that some WMDPDEs have a better performance than the MLE in relation to robustness. Two examples with multiple stresses show the usefulness of the model and, in particular, of the proposed estimators, both in engineering and medicine.

Topics & Concepts

EstimatorRobustness (evolution)Exponential functionM-estimatorMathematicsContext (archaeology)InferenceMaximum likelihoodStatisticsApplied mathematicsComputer scienceArtificial intelligenceMathematical analysisBiologyPaleontologyBiochemistryChemistryGeneStatistical Distribution Estimation and ApplicationsReliability and Maintenance OptimizationOptimal Experimental Design Methods
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