Asymptotics for Lasso - Type Estimators
نویسنده
چکیده
We consider the asymptotic behavior of regression estimators that minimize the residual sum of squares plus a penalty proportional to ∑ βj γ for some γ > 0. These estimators include the Lasso as a special case when γ = 1. Under appropriate conditions, we show that the limiting distributions can have positive probability mass at 0 when the true value of the parameter is 0. We also consider asymptotics for “nearly singular” designs.
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