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This paper illustrates how Bayesian networks and BayesiaLab can help overcome certain limitations of traditional statistical methods in highdimensional problem domains. We consider the vehicle safety discussion in the recent Final Rule, issued by the Environmental Protection Agency (EPA) and the National Highway Traffic Safety Administration (NHTSA) on future fuel economy standards, as an ideal topic for our demonstration purposes.
Extending beyond the traditional parametric methods employed in the EPA/NHTSA studies, we want to show how Bayesian networks can provide a powerful framework for forecasting the impact of regulatory intervention. Ultimately, we wish to use Bayesian networks for reasoning about consequences of actions not yet taken.
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