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초록·키워드 목차

Robust estimation is widely used for analyzing statistical inference. We investigate penalized robust estimation via Welsch loss function with group Lasso method in high-dimensional linear regression models with group structure in this paper. This penalty identifies the significant groups of predictor variables. Robust estimation with group Lasso has crucial meaning in that it accompanies the large p (the number of predictors) small n (sample size) problems. We present the updating algorithms for this group Lasso problem. Compared with other penalty functions, we carried out simulation studies in order to assess the performance of the proposed method and the real dataset was demonstrated numerically for illustration purpose. #Robust estimator #Welsch #penalized regression #group-Lasso #Huber

Abstract
1. Introduction
2. Robust estimation
3. Penalized estimation with group Lasso
4. Numerical study
5. Concluding remarks
References

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