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- W2543497395 abstract "Robust estimation often relies on a dispersion function that is more slowly varying at large values than the square function. However, the choice of tuning constant in dispersion functions may impact the estimation efficiency to a great extent. For a given family of dispersion functions such as the Huber family, we suggest obtaining the best tuning constant from the data so that the asymptotic efficiency is maximized. This data-driven approach can automatically adjust the value of the tuning constant to provide the necessary resistance against outliers. Simulation studies show that substantial efficiency can be gained by this data-dependent approach compared with the traditional approach in which the tuning constant is fixed. We briefly illustrate the proposed method using two datasets." @default.
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- W2543497395 date "2007-01-01" @default.
- W2543497395 modified "2023-10-08" @default.
- W2543497395 title "Robust estimation using the Huber function with a data-dependent tuning constant" @default.
- W2543497395 hasPublicationYear "2007" @default.
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