Estimator with zero expected error.

Converges to true value asymptotically.

Estimator's expected value deviates from true value.

Achieves lowest possible variance unbiasedly.

The ratio estimator is a statistical estimator for the ratio of means of two random variables.

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 statistics, the bias of an estimator (or bias function) is the difference between this estimator's expected value and the true value of the parameter being estimated.