In this paper we construct a class of minimum distance Cramer-von Mises-type estimators for the parameter in the first-order stationary autoregressive time series. The estimator is proved to be asymptotically normal under appropriate assumptions. The proofs involve some results of independent interest.
Publié le : 1986-09-14
Classification:
Randomly weighted empirical processes,
stationary and ergodic processes,
bounded functionals on $L_2$-spaces,
Lipschitz condition,
conditional expectation,
62L10
@article{1176350058,
author = {Wang, Chamont W. H.},
title = {A Minimum Distance Estimator for First-Order Autoregressive Processes},
journal = {Ann. Statist.},
volume = {14},
number = {2},
year = {1986},
pages = { 1180-1193},
language = {en},
url = {http://dml.mathdoc.fr/item/1176350058}
}
Wang, Chamont W. H. A Minimum Distance Estimator for First-Order Autoregressive Processes. Ann. Statist., Tome 14 (1986) no. 2, pp. 1180-1193. http://gdmltest.u-ga.fr/item/1176350058/