Abstract
Semiparametric spectral methods are valuable in that they yield inference on time series under very broad assumptions. This contribution analyzes the averaged periodogram statistic in the framework of a generalized linear process with (possibly long memory) conditional heteroscedasticity in the innovations. It is shown that the averaged periodogram statistic is appropriate for asymptotically normal estimation of the spectrum of a weakly dependent process at frequency zero and for consistent estimation of long memory and stationary cointegration in strongly dependent processes.
Translated title of the contribution | Spectral estimatioin with long memory conditional heteroscedasticity |
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Original language | French |
Pages (from-to) | 811-814 |
Number of pages | 4 |
Journal | Comptes Rendus de l'Academie des Sciences - Series I: Mathematics |
Volume | 329 |
Issue number | 9 |
DOIs | |
State | Published - Jan 1 1999 |
All Science Journal Classification (ASJC) codes
- Mathematics(all)