Confidence estimation with discrete reliability growth models

Abstract Interest in modeling reliability growth has motivated the introduction of discrete time versions of the Crow continuous time non-homogeneous Poisson process. The discrete reliability growth model applies to well defined trials that result in success or failure. Extending the results of Bhattacharyya, Fries and Johnson (1989) to unequal numbers of trials per equipment configuration, we investigate the large sample properties of some estimators that are analogous to those of the continuous model. Large sample confidence intervals are obtained for the parameters and the reliability at the last stage of testing.

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