Asymptotic theory for maximum likelihood estimation of the memory parameter in stationary Gaussian processes
Lieberman, O., Rosemarin, R. & Rousseau, J.
(2012).
Asymptotic theory for maximum likelihood estimation of the memory parameter in stationary Gaussian processes.
Econometric Theory,
28(02), 457-470.
https://doi.org/10.1017/S0266466611000399
Consistency, asymptotic normality, and efficiency of the maximum likelihood estimator for stationary Gaussian time series were shown to hold in the short memory case by Hannan (1973, Journal of Applied Probability 10, 130-145) and in the long memory case by Dahlhaus (1989, Annals of Statistics 34, 1045-1047). In this paper we extend these results to the entire stationarity region, including the case of antipersistence and noninvertibility.
| Item Type | Article |
|---|---|
| Departments | LSE > Academic Departments > Statistics |
| DOI | 10.1017/S0266466611000399 |
| Date Deposited | 19 Apr 2012 |
| URI | https://researchonline.lse.ac.uk/id/eprint/43173 |
Explore Further
- https://www.scopus.com/pages/publications/84859119148 (Scopus publication)
- http://journals.cambridge.org/action/displayJourna... (Official URL)