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Whittle parameter estimation for vector ARMA models with heavy-tailed noises.
- Source :
-
Journal of Statistical Planning & Inference . Jul2022, Vol. 219, p216-230. 15p. - Publication Year :
- 2022
-
Abstract
- This paper studies the Whittle estimation for vector autoregressive and moving average (ARMA) models with heavy-tailed noises. It is shown that the Whittle estimator is consistent with the rate of convergence n 1 / α L ̃ (n) and its limiting distribution is a function of two stable random vectors, where L ̃ (n) is a slowly varying function and α ∈ (0 , 2) is the tail index of heavy-tailed vector noise. A simulation study is carried out to assess the performance of this estimator in finite samples and a real example is given. This paper includes several limiting theorems for the general heavy-tailed vector processes, which is independent of interest. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 03783758
- Volume :
- 219
- Database :
- Academic Search Index
- Journal :
- Journal of Statistical Planning & Inference
- Publication Type :
- Academic Journal
- Accession number :
- 155149695
- Full Text :
- https://doi.org/10.1016/j.jspi.2021.12.003