Convergence results for maximum likelihood type estimators in multivariable ARMA models

Benedikt Pötscher

Journal of Multivariate Analysis, 1987, vol. 21, issue 1, 29-52

Abstract: General convergence results for maximum likelihood type estimators in multivariable ARMA-models under very weak assumptions are given. This extends results by Dunsmuir and Hannan (1976, Advan. Appl. Probab. 8 339-364) and Deistler, Dunsmuir, and Hannan (1978, Advan. Appl. Probab. 10 360-372). In particular it is shown that consistency can be achieved without imposing a certain assumption used in Dunsmuir and Hannan which is related to the zeroes of the spectral density if one is willing to make stronger assumptions concerning the probabilistic structure of the process.

Keywords: ARMA-model; likelihood-function; consistency; misspecification (search for similar items in EconPapers)
Date: 1987
References: Add references at CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0047-259X(87)90097-2
Full text for ScienceDirect subscribers only

Related works:
Journal Article: Convergence results for maximum likelihood type estimators in multivariable ARMA models II (1989)
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:eee:jmvana:v:21:y:1987:i:1:p:29-52

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Journal of Multivariate Analysis is currently edited by de Leeuw, J.

More articles in Journal of Multivariate Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().