SOME ASYMPTOTIC PROPERTIES OF THE SAMPLE COVARIANCES OF GAUSSIAN AUTOREGRESSIVE MOVING‐AVERAGE PROCESSES

Boaz Porat

Journal of Time Series Analysis, 1987, vol. 8, issue 2, 205-220

Abstract: Abstract. The paper deals with the asymptotic variances of the sample covariances of autoregressive moving average processes. Using state‐space representations and some matrix Lyapunov equation theory, closed‐form expressions are derived for the asymptotic variances of the sample covariances and for the Cramer‐Rao bounds on the process covariances. The main results obtained from these expressions are as follows: For ARMA (p, q) processes with p≥q, the sample covariance of order n is asymptotically efficient if and only if 0 ≤n≤p – q. For ARMA (p, q) processes with p

Date: 1987
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://doi.org/10.1111/j.1467-9892.1987.tb00433.x

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jtsera:v:8:y:1987:i:2:p:205-220

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0143-9782

Access Statistics for this article

Journal of Time Series Analysis is currently edited by M.B. Priestley

More articles in Journal of Time Series Analysis from Wiley Blackwell
Bibliographic data for series maintained by Wiley Content Delivery ().