Balakrishnan, NarayanaswamyCastilla González, Elena MaríaMartín Apaolaza, NirianPardo Llorente, Leandro2023-06-172023-06-172020-05-200748-801710.1002/qre.2665https://hdl.handle.net/20.500.14352/7223"This is the pre-peer reviewed version of the following article: Balakrishnan, N, Castilla, E, Martín, N, Pardo, L. Robust inference for one-shot device testing data under exponential lifetime model with multiple stresses. Qual Reliab Engng Int. 2020; 36: 1916-1930 , which has been published in final form at https://doi.org/10.1002/qre.2665. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions."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.engAtribución-NoComercial 3.0 Españahttps://creativecommons.org/licenses/by-nc/3.0/es/journal articlehttps://doi.org/10.1002/qre.2665https://onlinelibrary.wiley.com/doi/full/10.1002/qre.2665open access519.2Exponential distributionMinimum density power divergence estimatorMultiple stressesOne-shot devicesRobustnessWald-type testsEstadística matemática (Matemáticas)Probabilidades (Matemáticas)1209 Estadística