A Goodness-of-Fit Procedure for Testing Whether a Reliability Growth Model Fits Data That Show Improvement
Reliability growth models that have been discussed in the literature generally assume that an item (such as a piece of electronic equipment) is tested in stages a given number of times, ni (say, at the ith stage, i = l,2,.,,,k) If, at the ith stage, xi successes are recorded (and hence ni - xi failures), the problem is then simply to estimate pi, the probability of success at the ith stage, i= 1,2,…,k. It is assumed that stages are independent of each other and of time. In this article a general parametric reliability growth model is proposed for pi and a goodness-of-fit test based on the likelihood ratio criterion is proposed. This test is carried out on data that show reliability growth in stages to determine the adequacy of the fit of the proposed reliability growth model.
Key Wordslikelihood ratio test maximum likelihood estimators stochastic expansions chi-square statistics
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