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Robust estimation and hypothesis testing under short-tailedness and inliers

2005-06-01
Akkaya, Ayşen
Tiku, ML
Estimation and hypothesis testing based on normal samples censored in the middle are developed and shown to be remarkably efficient and robust to symmetric short-tailed distributions and to inliers in a sample. This negates the perception that sample mean and variance are the best robust estimators in such situations (Tiku, 1980; Dunnett, 1982).