Access the full text.
Sign up today, get DeepDyve free for 14 days.
Loading next page...
/lp/springer-journals/asymptotic-behavior-of-iterative-m-estimartors-for-location-y54Mx04Bjn
References (15)
-
F. Hampel (1974)
The Influence Curve and Its Role in Robust EstimationJournal of the American Statistical Association, 69
-
D. Hinkley, D. Andrews, P. Bickel, F. Hampel, P. Huber, W. Rogers, J. Tukey (1975)
Robust Estimates of Location: Survey and Advances., 136
-
V. Yohai, R. Maronna (1979)
ASYMPTOTIC BEHAVIOR OF M-ESTIMATORS FOR THE LINEAR MODELAnnals of Statistics, 7
-
P. Huber (1973)
Robust Regression: Asymptotics, Conjectures and Monte CarloAnnals of Statistics, 1
-
R. Berk (1967)
A Special Structure and Equivariant EstimationAnn. Math. Statist., 38
-
P. Bickel (1975)
One-Step Huber Estimates in the Linear ModelJournal of the American Statistical Association, 70
-
V. Yohai (1974)
Robust Estimation in the Linear ModelAnnals of Statistics, 2
-
R. Dutter (1975)
Robust Regression: Different Approaches to Numerical Solutions and Algorithms -
R. Berk (1967)
A Special Group Structure and Equivariant EstimationAnnals of Mathematical Statistics, 38
-
D. Relles (1969)
Robust regression by modified least-squares -
K. Alam (1971)
Estimation of a Location Parameter -
F. Hampel (1968)
Contributions to the theory of robust estimation -
P. Huber (1964)
Robust Estimation of a Location ParameterAnnals of Mathematical Statistics, 35
-
P. Huber (1967)
The behavior of maximum likelihood estimates under nonstandard conditions -
J. Collins (1976)
Robust Estimation of a Location Parameter in the Presence of AsymmetryAnnals of Statistics, 4
- Publisher
- Springer Journals
- Copyright
- Copyright © 1979 by Sociedade Brasileira de Matemática
- Subject
- Mathematics; Mathematics, general; Theoretical, Mathematical and Computational Physics
- ISSN
- 1678-7544
- eISSN
- 1678-7714
- DOI
- 10.1007/BF02588338
- Publisher site
- See Article on Publisher Site
Abstract
In this paper, we study the Huber M-estimator for location when they are computed by a class of numerical iterative procedures. This class includes the usual method of Newton-Raphson, iterated weighted least squares and iterated winsorization. We show that under mild conditions, the numerical iterative procedures converge and the resulting estimators are consistent and asymptotically normal.
Journal
Bulletin of the Brazilian Mathematical Society, New Series – Springer Journals
Published: Mar 11, 2007