Weak convergence of the sequential empirical processes of residuals in nonstationary autoregressive models
Ling, Shiqing
Ann. Statist., Tome 26 (1998) no. 3, p. 741-754 / Harvested from Project Euclid
This paper establishes the weak convergence of the sequential empirical process $\hat{K}_n$ of the estimated residuals in nonstationary autoregressive models. Under some regular conditions, it is shown that $\hat{K}_n$ converges weakly to a Kiefer process when the characteristic polynomial does not include the unit root 1; otherwise $\hat{K}_n$ converges weakly to a Kiefer process plus a functional of stochastic integrals in terms of the standard Brownian motion. The latter differs not only from that given by Koul and Levental for an explosive AR(1) model but also from that given by Bai for a stationary ARMA model.
Publié le : 1998-04-14
Classification:  Brownian motions,  Kiefer process,  sequential empirical processes,  nonstationary autoregressive model,  weak convergence,  62G30,  60F17,  62M10,  62F05
@article{1028144857,
     author = {Ling, Shiqing},
     title = {Weak convergence of the sequential empirical processes of residuals in nonstationary autoregressive models},
     journal = {Ann. Statist.},
     volume = {26},
     number = {3},
     year = {1998},
     pages = { 741-754},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1028144857}
}
Ling, Shiqing. Weak convergence of the sequential empirical processes of residuals in nonstationary autoregressive models. Ann. Statist., Tome 26 (1998) no. 3, pp.  741-754. http://gdmltest.u-ga.fr/item/1028144857/