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  2. Unbiased estimation of standard deviation - Wikipedia

    en.wikipedia.org/wiki/Unbiased_estimation_of...

    which is an unbiased estimator of the variance of the mean in terms of the observed sample variance and known quantities. If the autocorrelations are identically zero, this expression reduces to the well-known result for the variance of the mean for independent data. The effect of the expectation operator in these expressions is that the ...

  3. Bias of an estimator - Wikipedia

    en.wikipedia.org/wiki/Bias_of_an_estimator

    The theory of median-unbiased estimators was revived by George W. Brown in 1947: [8]. An estimate of a one-dimensional parameter θ will be said to be median-unbiased, if, for fixed θ, the median of the distribution of the estimate is at the value θ; i.e., the estimate underestimates just as often as it overestimates.

  4. Minimum-variance unbiased estimator - Wikipedia

    en.wikipedia.org/wiki/Minimum-variance_unbiased...

    In statistics a minimum-variance unbiased estimator (MVUE) or uniformly minimum-variance unbiased estimator (UMVUE) is an unbiased estimator that has lower variance than any other unbiased estimator for all possible values of the parameter.

  5. Variance - Wikipedia

    en.wikipedia.org/wiki/Variance

    The unbiased estimation of standard deviation is a technically involved problem, though for the normal distribution using the term n − 1.5 yields an almost unbiased estimator. The unbiased sample variance is a U-statistic for the function ƒ(y 1, y 2) = (y 1 − y 2) 2 /2, meaning that it is obtained by averaging a 2-sample statistic over 2 ...

  6. Algorithms for calculating variance - Wikipedia

    en.wikipedia.org/wiki/Algorithms_for_calculating...

    Based on this sample, the estimated population mean is 10, and the unbiased estimate of population variance is 30. Both the naïve algorithm and two-pass algorithm compute these values correctly. Next consider the sample (10 8 + 4, 10 8 + 7, 10 8 + 13, 10 8 + 16), which gives rise to the same estimated variance as the first sample. The two-pass ...

  7. U-statistic - Wikipedia

    en.wikipedia.org/wiki/U-statistic

    For example, a single observation is itself an unbiased estimate of the mean and a pair of observations can be used to derive an unbiased estimate of the variance. The U-statistic based on this estimator is defined as the average (across all combinatorial selections of the given size from the full set of observations) of the basic estimator ...

  8. Estimator - Wikipedia

    en.wikipedia.org/wiki/Estimator

    Among unbiased estimators, there often exists one with the lowest variance, called the minimum variance unbiased estimator . In some cases an unbiased efficient estimator exists, which, in addition to having the lowest variance among unbiased estimators, satisfies the Cramér–Rao bound , which is an absolute lower bound on variance for ...

  9. Efficiency (statistics) - Wikipedia

    en.wikipedia.org/wiki/Efficiency_(statistics)

    The Cramér–Rao lower bound is a lower bound of the variance of an unbiased estimator, representing the "best" an unbiased estimator can be. An efficient estimator is also the minimum variance unbiased estimator (MVUE). This is because an efficient estimator maintains equality on the Cramér–Rao inequality for all parameter values, which ...