In a framework particularly suited for many time-series models we obtain a LAN result under quite natural and economical conditions. This enables us to construct adaptive estimators for (part of) the Euclidean parameter in these semiparametric models. Special attention is directed to group models in time series with the important subclass of models with time varying location and scale. Our set-up is confronted with the existing literature and, as examples, we reconsider linear regression and ARMA, TAR and ARCH models.
Publié le : 1997-04-14
Classification:
LAN in time series,
adaptive estimation,
semiparametrics,
62G05,
62F12,
62M10
@article{1031833674,
author = {Drost, Feike C. and Klaassen, Chris A. J. and Werker, Bas J. M.},
title = {Adaptive estimation in time-series models},
journal = {Ann. Statist.},
volume = {25},
number = {6},
year = {1997},
pages = { 786-817},
language = {en},
url = {http://dml.mathdoc.fr/item/1031833674}
}
Drost, Feike C.; Klaassen, Chris A. J.; Werker, Bas J. M. Adaptive estimation in time-series models. Ann. Statist., Tome 25 (1997) no. 6, pp. 786-817. http://gdmltest.u-ga.fr/item/1031833674/