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Probabilistic Risk Analysis and Bayesian Decision Theory

In: Bayesian Compendium

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  • Marcel van Oijen

Abstract

As Bayesians, we try to acknowledge all our uncertainties about data and models, and express them as probability distributions. As we have seen in the preceding chapters, this approach allows us to quantify predictive uncertainty when using our models to predict the future. And this is of course important for the user of these predictions, whether that user is us or someone whom we report our results to. Our probabilistic results allow not just prediction but also calculation of risks and, more generally, support for decision-making.

Suggested Citation

  • Marcel van Oijen, 2020. "Probabilistic Risk Analysis and Bayesian Decision Theory," Springer Books, in: Bayesian Compendium, chapter 0, pages 129-133, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-55897-0_17
    DOI: 10.1007/978-3-030-55897-0_17
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