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- W2339982878 abstract "SUMMARY Under the simple linear regression model, we consider two violations of the standard assumptions, namely heterogeneous variances and long-tailed error distributions, in an integrated manner. A new method for estimation is proposed which assumes only that the heterogeneity is a locally smooth function of the regressor variable, except for outliers. The procedure is based on smoothing the nonoutlying residuals from a robust regression to provide weights for a weighted regression. Monte Carlo results, some theory and a real data example are given. It is shown that the method is substantially more efficient than the usual robust regression methods in the presence of heterogeneity and only slightly worse when the variances are exactly equal." @default.
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- W2339982878 date "1993-01-01" @default.
- W2339982878 modified "2023-10-14" @default.
- W2339982878 title "Robust, Smoothly Heterogeneous Variance Regression" @default.
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- W2339982878 doi "https://doi.org/10.2307/2986237" @default.
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