What is it about?
The mean can be spoiled by few wrong observations. We look for different method, which gets rid of these bad observations but preserves the simplicity comparable to median.
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Why is it important?
It can help to improve the quality of an estimator of parameter of location.
Read the Original
This page is a summary of: Robust estimators based on generalization of trimmed mean, Communications in Statistics - Simulation and Computation, June 2017, Taylor & Francis,
DOI: 10.1080/03610918.2017.1337136.
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