The Annals of Statistics
- Ann. Statist.
- Volume 20, Number 3 (1992), 1514-1533.
Asymptotics for $M$-Estimators Defined by Convex Minimization
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.
Article information
Source
Ann. Statist., Volume 20, Number 3 (1992), 1514-1533.
Dates
First available in Project Euclid: 12 April 2007
Permanent link to this document
https://projecteuclid.org/euclid.aos/1176348782
Digital Object Identifier
doi:10.1214/aos/1176348782
Mathematical Reviews number (MathSciNet)
MR1186263
Zentralblatt MATH identifier
0786.62040
JSTOR
links.jstor.org
Subjects
Primary: 62F12: Asymptotic properties of estimators
Secondary: 62F20
Keywords
$M$-estimation convex minimization asymptotics least absolute deviations Bahadur representation
Citation
Niemiro, Wojciech. Asymptotics for $M$-Estimators Defined by Convex Minimization. Ann. Statist. 20 (1992), no. 3, 1514--1533. doi:10.1214/aos/1176348782. https://projecteuclid.org/euclid.aos/1176348782
