Trimmed Estimator

In statistics, a trimmed estimator is an estimator derived from another estimator by excluding some of the extreme values. This is generally done to obtain a more robust statistic, and the extreme values are considered outliers. Trimmed estimators also often have higher efficiency for mixture distributions and heavy-tailed distributions than the corresponding untrimmed estimator, at the cost of lower efficiency for other distributions, such as the normal distribution.

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. In some cases a trimmed estimator discards a fixed number of points (such as maximum and minimum) instead of a percentage.