Statistical decision theory

Summary

Statistical decision theory treats statistical problems as decisions under uncertainty. A statistician observes data from a model with an unknown parameter and chooses an action by a decision rule. The statistician then pays a loss that depends on the action and the true parameter. Rules are compared through their risk functions, which gives a common frame for estimation, testing and prediction.