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Decision Theory: Course Outline

The course intends to provide a general overview of the structure and the representation of preferences using Bayesian Statistics in the context of multi criteria decision making, from the study of aggregation functions to the Analytic Hierarchy Process (

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Course Outline

  • Utility.
  • Rewards.
  • Consequences and decision function.
  • Game theoretic interpretation of Statistical estimation and testing.
  • Admissibility  of Bayesian procedures. 
  • The complete class theorem. 
  • The minimax theorem. 
  • Randomization in one game theory.
  • Difference from Bayesian approach.
  • Invariance and minimaxity.
  • Admissibility of invariant rules.
  • Location and  scale invariance.
  • Pitman estimators.

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