In a regression model with an error that is a general linear process, the second-order expansion of the risk matrix of GLSE or MLE is obtained. a set of sufficient conditions for the effect of estimating the structural parameter of the linear process to vanish in the above expasion is obtained. The relation of the covariance matrix of SLSE with those of GLSE and MLE up to $O(T^-2)$ is elucidated.
Publié le : 1986-09-14
Classification:
GLSE,
Grenander's condition,
linear process,
MLE,
regression with a linear process,
second-order risk,
SLSE,
62F10,
62J10
@article{1176350060,
author = {Toyooka, Yasuyuki},
title = {Second-Order Risk Structure of GLSE and MLE in a Regression with a Linear Process},
journal = {Ann. Statist.},
volume = {14},
number = {2},
year = {1986},
pages = { 1214-1225},
language = {en},
url = {http://dml.mathdoc.fr/item/1176350060}
}
Toyooka, Yasuyuki. Second-Order Risk Structure of GLSE and MLE in a Regression with a Linear Process. Ann. Statist., Tome 14 (1986) no. 2, pp. 1214-1225. http://gdmltest.u-ga.fr/item/1176350060/