User:Katnap1/sandbox

Within statistical decision theory, Γ-minimax theory deals with the problem of selecting decision rules under partial prior information on the distribution of the unknown parameter. The selected rule is the one minimizing the supremum of the payoff (Bayes and regret risk in a frequentist approach, and posterior expected loss and regret in a Bayesian one) over the priors in Γ.