Speaker
Jonas Kristoffer Lindeløv
(Department of Communication and Psychology, Aalborg University, Denmark)
Description
Utility Theory allow you to make optimal decisions in the face of uncertainty. For example, what bidding price would maximize your earnings, taking the chance of failure into account? Utility Theory latches nicely onto Bayesian Inference. Once you have a posterior distribution, you need only a few more lines of code to apply a utility function (aka loss function) and identify the decision that optimizes said utility. This approach scales well to more complex models and decisions. We will use R and rstanarm/brms for Bayesian inference and hand-code the utility. An R notebook with worked examples will accompany the tutorial.
Primary author
Jonas Kristoffer Lindeløv
(Department of Communication and Psychology, Aalborg University, Denmark)
