Bayesian methodology for reliability model acceptance

The different types of uncertainties are considered and their differences are identified. Various methods of statistical analysis of data are reviewed and their usefulness and domain of applicability are identified. The common methods of representing model uncertainties are indicated and several examples of assessment of model uncertainties indicate how the principles described can be applied.

Quantification of Model Uncertainty in Structural Reliability

In the development of techniques for software reliability measurement and prediction, many software reliability growth models have been proposed. Application of these models to real data sources has shown that there is commonly great disagreement in predictions, while none of them has been shown to be more trustworthy than others in terms of predictive quality in all applications. Recent work has largely overcome this problem through the development of specialized techniques which analyse the accuracy of predictions from reliability models. Such techniques allow the user to choose, for future predictions for a particular data source, those models which gave the best predictions in the past, for this data.

Combination of Predictions Obtained from Different Software Reliability Growth Models

Bibliography of literature on reliability in civil engineering

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A Bayesian procedure for drawing inferences from random data