Balakrishnan, NarayanaswamyCastilla González, Elena MaríaMartín Apaolaza, NirianPardo Llorente, Leandro2024-01-172024-01-172020-09N. Balakrishnan, E. Castilla, N. Martín and L. Pardo, "Robust Inference for One-Shot Device Testing Data Under Weibull Lifetime Model," in IEEE Transactions on Reliability, vol. 69, no. 3, pp. 937-953, Sept. 2020, doi: 10.1109/TR.2019.2954385.10.1109/TR.2019.2954385https://hdl.handle.net/20.500.14352/93697Classical inferential methods for one-shot device testing data from an accelerated life-test are based on maximum likelihood estimators (MLEs) of model parameters. However, the lack of robustness of MLE is well-known. In this article, we develop robust estimators for one-shot device testing by assuming a Weibull distribution as a lifetime model. Wald-type tests based on these estimators are also developed. Their robustness properties are evaluated both theoretically and empirically, through an extensive simulation study. Finally, the methods of inference proposed are applied to three numerical examples. Results obtained from both Monte Carlo simulations and numerical studies show the proposed estimators to be a robust alternative to MLEs.engAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/journal articlehttps//doi.org/10.1109/TR.2019.2954385https://ieeexplore.ieee.org/document/8922869open accessExponential distributionMinimum density power divergence (DPD) estimatorOne-shot devicesRobustnessWald-type testsCiencias1209 Estadística