Probabilistic Risk Analysis and Bayesian Decision Theory

Marcel van Oijen ()

Chapter Chapter 17 in Bayesian Compendium, 2020, pp 129-133 from Springer

Abstract: 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.

Date: 2020
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DOI: 10.1007/978-3-030-55897-0_17

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