Asymptotically efficient (adaptive) estimators for the slope parameters of the linear regression model are constructed based upon the "regression quantile" statistics suggested by Koenker and Bassett. The estimators are natural analogues of the adaptive $L$-estimators of location of Sacks, but employ kernel-density type estimators of the optimal $L$-estimator weight function.
Publié le : 1989-03-14
Classification:
Regression quantiles,
kernel-density estimation,
adaptive estimation,
linear models,
62J05,
62G35,
62F20
@article{1176347022,
author = {Portnoy, Stephen and Koenker, Roger},
title = {Adaptive $L$-Estimation for Linear Models},
journal = {Ann. Statist.},
volume = {17},
number = {1},
year = {1989},
pages = { 362-381},
language = {en},
url = {http://dml.mathdoc.fr/item/1176347022}
}
Portnoy, Stephen; Koenker, Roger. Adaptive $L$-Estimation for Linear Models. Ann. Statist., Tome 17 (1989) no. 1, pp. 362-381. http://gdmltest.u-ga.fr/item/1176347022/