Asymptotic results for multivariate local Whittle estimation with applications
Düker MC, Pipiras V (2019)
Publication Type: Conference contribution
Publication year: 2019
Publisher: Institute of Electrical and Electronics Engineers Inc.
Pages Range: 584-588
Conference Proceedings Title: 2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2019 - Proceedings
Event location: Le Gosier, GLP
ISBN: 9781728155494
DOI: 10.1109/CAMSAP45676.2019.9022642
Abstract
The asymptotic normality result is obtained for local Whittle estimators of all model parameters in a general formulation of multivariate long memory. The result is then used in devising a global statistical test for the so-called fractal non-connectivity, and in deriving the asymptotics of LASSO estimators of parameters in the so-called long-run variance matrix and its inverse. Some numerical illustrations are also provided.
Authors with CRIS profile
Involved external institutions
Ruhr-Universität Bochum (RUB)
Germany (DE)
University of North Carolina at Chapel Hill
United States (USA) (US)
Germany (DE)
University of North Carolina at Chapel Hill
United States (USA) (US)
How to cite
APA:
Düker, M.C., & Pipiras, V. (2019). Asymptotic results for multivariate local Whittle estimation with applications. In 2019 IEEE 8th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2019 - Proceedings (pp. 584-588). Le Gosier, GLP: Institute of Electrical and Electronics Engineers Inc..
MLA:
Düker, Marie Christine, and Vladas Pipiras. "Asymptotic results for multivariate local Whittle estimation with applications." Proceedings of the 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, CAMSAP 2019, Le Gosier, GLP Institute of Electrical and Electronics Engineers Inc., 2019. 584-588.
BibTeX: Download