The problem of testing linear hypotheses about the parameter vector of an autoregressive process with finite order is considered. Based on the property of local asymptotic normality, we derive asymptotically optimal statistical tests. Additionally, we define and investigate so-called residual rank tests. For these tests we obtain under the null hypothesis an asymptotic distribution which does not depend on the distribution of the innovation.
Publié le : 1990-09-14
Classification:
Autoregressive process,
testing linear hypotheses,
local asymptotic normality,
ranked residuals,
asymptotic distribution,
62F03,
62F05,
62M10,
62F07,
62F35
@article{1176347762,
author = {Kreiss, Jens-Peter},
title = {Testing Linear Hypotheses in Autoregressions},
journal = {Ann. Statist.},
volume = {18},
number = {1},
year = {1990},
pages = { 1470-1482},
language = {en},
url = {http://dml.mathdoc.fr/item/1176347762}
}
Kreiss, Jens-Peter. Testing Linear Hypotheses in Autoregressions. Ann. Statist., Tome 18 (1990) no. 1, pp. 1470-1482. http://gdmltest.u-ga.fr/item/1176347762/