### Some articles on *unbiased, unbiased estimator, estimator*:

Stein's Unbiased Risk Estimate

... In statistics, Stein's

... In statistics, Stein's

**unbiased**risk estimate (SURE) is an**unbiased estimator**of the mean-squared error of "a nearly arbitrary, nonlinear biased**estimator**." In other words, it provides an ... This is important since the true mean-squared error of an**estimator**is a function of the unknown parameter to be estimated, and thus cannot be determined exactly ...Minimum-variance

... In statistics a uniformly minimum-variance

**Unbiased Estimator**... In statistics a uniformly minimum-variance

**unbiased estimator**or minimum-variance**unbiased estimator**(UMVUE or MVUE) is an**unbiased estimator**that has lower variance ...Bias Of An Estimator - Examples - Estimating A Poisson Probability

... A far more extreme case of a biased

... A far more extreme case of a biased

**estimator**being better than any**unbiased estimator**arises from the Poisson distribution ... calls arrive in the next two minutes.) Since the expectation of an**unbiased estimator**δ(X) is equal to the estimand, i.e the only function of the data constituting ... The (biased) maximum likelihood**estimator**is far better than this**unbiased estimator**...Sample Maximum And Minimum - Applications - Estimation - Uniform Distribution

... are sufficient and complete statistics for the unknown endpoints thus an

... are sufficient and complete statistics for the unknown endpoints thus an

**unbiased estimator**derived from these will be UMVU**estimator**... If only the top endpoint is unknown, the sample maximum is a biased**estimator**for the population maximum, but the**unbiased estimator**(where m is the sample maximum and k is the sample ... both endpoints are unknown, then the sample range is a biased**estimator**for the population range, but correcting as for maximum above yields the UMVU**estimator**...Bessel's Correction

... the population mean is unknown, the sample variance is a biased

... the population mean is unknown, the sample variance is a biased

**estimator**of the population variance, and systematically underestimates it ... using 1/(n − 1) instead of 1/n in the**estimator**'s formula) corrects for this, and gives an**unbiased estimator**of the population variance ... The cost of this correction is that the**unbiased estimator**has uniformly higher mean squared error than the biased**estimator**...### Famous quotes containing the word unbiased:

“There is not a more disgusting spectacle under the sun than our subserviency to British criticism. It is disgusting, first, because it is truckling, servile, pusillanimous—secondly, because of its gross irrationality. We know the British to bear us little but ill will—we know that, in no case do they utter *unbiased* opinions of American books ... we know all this, and yet, day after day, submit our necks to the degrading yoke of the crudest opinion that emanates from the fatherland.”

—Edgar Allan Poe (1809–1845)

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