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.
| 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 |
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All Science Journal Classification (ASJC) codes
- Mathematics(all)
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Estimation spectrale avec mémoire longue et hétéroscédasticité conditionnelle. / Henry, Marc Albert.
In: Comptes Rendus de l'Academie des Sciences - Series I: Mathematics, Vol. 329, No. 9, 01.01.1999, p. 811-814.Research output: Contribution to journal › Article
TY - JOUR
T1 - Estimation spectrale avec mémoire longue et hétéroscédasticité conditionnelle
AU - Henry, Marc Albert
PY - 1999/1/1
Y1 - 1999/1/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=17144448570&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=17144448570&partnerID=8YFLogxK
U2 - 10.1016/S0764-4442(99)90013-7
DO - 10.1016/S0764-4442(99)90013-7
M3 - Article
AN - SCOPUS:17144448570
VL - 329
SP - 811
EP - 814
JO - Comptes Rendus Mathematique
JF - Comptes Rendus Mathematique
SN - 1631-073X
IS - 9
ER -