Asymptotic risk and phase transition of $l_{1}$-penalized robust estimator
ℓ₁惩罚稳健估计量的渐近风险与相变
Mean square error (MSE) of the estimator can be used to evaluate the performance of a regression model. In this paper, we derive the asymptotic MSE of $l_{1}$-penalized robust estimators in the limit of both sample size $n$ and dimension $p$ going to infinity with fixed ratio $n/p\rightarrow \delta $. We focus on the $l_{1}$-penalized least absolute deviation and $l_{1}$-penalized Huber’s regressions. Our analytic study shows the appearance of a sharp phase transition in the…