In statistical decision theory, where we are faced with the problem of estimating a deterministic parameter (vector) from observations an estimator (estimation rule) is called minimax if its maximal risk is minimal among all estimators of . In a sense this means that is an estimator which performs best in the worst possible case allowed in the problem.