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- W1567335713 abstract "<!-- *** Custom HTML *** --> We study the asymptotic properties of the SCAD-penalized least squares estimator in sparse, high-dimensional, linear regression models when the number of covariates may increase with the sample size. We are particularly interested in the use of this estimator for simultaneous variable selection and estimation. We show that under appropriate conditions, the SCAD-penalized least squares estimator is consistent for variable selection and that the estimators of nonzero coefficients have the same asymptotic distribution as they would have if the zero coefficients were known in advance. Simulation studies indicate that this estimator performs well in terms of variable selection and estimation." @default.
- W1567335713 created "2016-06-24" @default.
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- W1567335713 date "2007-01-01" @default.
- W1567335713 modified "2023-10-04" @default.
- W1567335713 title "Asymptotic oracle properties of SCAD-penalized least squares estimators" @default.
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- W1567335713 doi "https://doi.org/10.1214/074921707000000337" @default.
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