Dimitriou-Fakalou, C. (2009) Modified Gaussian Likelihood Estimators for ARMA models on $\mathbb{Z}^d$. Stochastic Processes and their Applications, 119 (12). pp. 4149-4175. ISSN 0304-4149.
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| Official URL http://dx.doi.org/10.1016/j.spa.2009.09.008 |
Abstract
For observations from an auto-regressive moving-average process on any number of dimensions, we propose a modification of the Gaussian likelihood, which when maximized corrects the edge-effects and fixes the order of the bias for the estimators derived. We show that the new estimators are not only consistent but also asymptotically normal for any dimensionality. A classical one-dimensional, time series result for the variance matrix is established on any number of dimensions and guarantees the efficiency of the estimators, if the original process is Gaussian. We have followed a model-based approach and we have used finite numbers for the corrections per dimension, which are especially made for the case of the auto-regressive moving-average models of fixed order.
| Item Type: | Article |
|---|---|
| Uncontrolled keywords: | Auto-regressive moving-average model; Edge-effect; Maximum likelihood estimation; Second-order properties |
| Subjects: | Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics |
| Divisions: | Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science > Statistics |
| Depositing User: | Chrysoula Dimitriou Fakalou |
| Date Deposited: | 10 Oct 2012 13:23 |
| Last Modified: | 12 Feb 2013 11:38 |
| Resource URI: | http://kar.kent.ac.uk/id/eprint/31487 (The current URI for this page, for reference purposes) |
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