Trimmed Estimator
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High Quality Content by WIKIPEDIA articles! Given a estimator, a trimmed estimator is obtained by excluding some of the extreme values. This is generally done to obtain a more robust statistic: the extreme values are considered outliers. Given an estimator, the n% trimmed version is obtained by discarding the n% lowest and highest observations: it is a statistic on the middle of the data. For instance, the 5% trimmed mean is obtained by taking the mean of the 2.5% to 97.5% range. Quantiles can be thought of as trimmed maximums or minimums: for instance, the 5th percentile is the 5% trimmed minimum.…mehr

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High Quality Content by WIKIPEDIA articles! Given a estimator, a trimmed estimator is obtained by excluding some of the extreme values. This is generally done to obtain a more robust statistic: the extreme values are considered outliers. Given an estimator, the n% trimmed version is obtained by discarding the n% lowest and highest observations: it is a statistic on the middle of the data. For instance, the 5% trimmed mean is obtained by taking the mean of the 2.5% to 97.5% range. Quantiles can be thought of as trimmed maximums or minimums: for instance, the 5th percentile is the 5% trimmed minimum.