Unbiased Estimator

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Unbiased Estimator

A mathematical estimation of the value of some unknown that does not differ from the unknown's true value.
References in periodicals archive ?
The jackknife technique was originally developed by Quenouille to reduce the bias of an estimator in a finite-population context.
If the data were, in fact, the population, the coverage probability of a confidence interval and the bias of an estimator could be computed with arbitrary accuracy by Monte Carlo simulation.
This section explains how the bootstrap can be used to reduce the bias of an estimator and why the bootstrap often provides an approximation to the coverage probability of a confidence interval that is more accurate than the approximation of asymptotic distribution theory.