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).
Citation Formats
A. Akkaya and M. Tiku, “Robust estimation and hypothesis testing under short-tailedness and inliers,” TEST, vol. 14, no. 1, pp. 129–150, 2005, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/34867.