Abstract
This paper develops a discrete reliability growth (RG) model for an inverse sampling scheme, e.g., for destructive tests of expensive single-shot operations systems where design changes are made only and immediately after the occurrence of failures. For qi, the probability of failure at the i-th stage, a specific parametric form is chosen which conforms to the concept of the Duane (1964, IEEE Trans. Aerospace Electron. Systems, 2, 563-566) learning curve in the continuous-time RG setting. A generalized linear model approach is pursued which efficiently handles a certain non-standard situation arising in the study of large-sample properties of the maximum likelihood estimators (MLEs) of the parameters. Alternative closed-form estimators of the model parameters are proposed and compared with the MLEs through asymptotic efficiency as well as small and moderate sample size simulation studies.
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Sen, A., Fries, A. Estimation in a Discrete Reliability Growth Model Under an Inverse Sampling Scheme. Annals of the Institute of Statistical Mathematics 49, 211–229 (1997). https://doi.org/10.1023/A:1003102610918
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DOI: https://doi.org/10.1023/A:1003102610918