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A commonly voiced concern with the Bayes factor is that, unlike many other Bayesian and non-Bayesian quantitative measures of model evaluation, it is highly sensitive to the parameter prior. This paper argues that, when dealing with psychological models that are quantitatively instantiated theories, being sensitive to the prior is an attractive feature of a model evaluation measure. This assertion...
In this paper, we introduce our practice of building Bayesian networks for airplane subsystem diagnosis. We use an efficient sensitivity analysis method to validate our diagnostic models. The algorithm is based on relevance-based decomposition in joint tree computation framework. We also describe how to use sensitivity analysis in model elicitation procedure to validate Bayesian network models based...
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