Asymptotics for $M$-Estimators Defined by Convex Minimization
The Annals of Statistics · 1992 · Volume 20 · Issue 3
Abstract
We consider $M$-estimators defined by minimization of a convex criterion function, not necessarily smooth. Our asymptotic results generalize some of those concerning the LAD estimators. We establish a Bahadur-type strong approximation and bounds on the rate of convergence.
Keywords
$M$-estimation; 62F12; 62F20; asymptotics; Bahadur representation; convex minimization; least absolute deviations;
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