Alj, A. and Azrak, R. and Ley, C. and Mélard, G. (2017) Asymptotic Properties of QML Estimators for VARMA Models with Time-dependent Coefficients. Scandinavian Journal of Statistics, 44 (3). pp. 617-635.

Full text not available from this repository.
Official URL:


This paper is about vector autoregressive-moving average models with time-dependent coefficients to represent non-stationary time series. Contrary to other papers in the univariate case, the coefficients depend on time but not on the series' length n. Under appropriate assumptions, it is shown that a Gaussian quasi-maximum likelihood estimator is almost surely consistent and asymptotically normal. The theoretical results are illustrated by means of two examples of bivariate processes. It is shown that the assumptions underlying the theoretical results apply. In the second example, the innovations are marginally heteroscedastic with a correlation ranging from −0.8 to 0.8. In the two examples, the asymptotic information matrix is obtained in the Gaussian case. Finally, the finite-sample behaviour is checked via a Monte Carlo simulation study for n from 25 to 400. The results confirm the validity of the asymptotic properties even for short series and the asymptotic information matrix deduced from the theory. © 2017 Board of the Foundation of the Scandinavian Journal of Statistics

Item Type: Article
Subjects: Decision Sciences
Divisions: SCIENTIFIC PRODUCTION > Decision Sciences
Depositing User: Administrateur Eprints Administrateur Eprints
Last Modified: 31 Jan 2020 15:46

Actions (login required)

View Item View Item