Characterization of periodically correlated and multivariate stationary discrete time wide Markov processes

Glaysar Castro and Valerie Girardin

Statistics & Probability Letters, 2008, vol. 78, issue 2, 158-164

Abstract: The aim of this paper is to give an overview of the structure of the class of discrete time wide Markov processes, either periodically correlated or multivariate stationary. We show many properties of their covariance, correlation and reflection coefficients matrices. We characterize these processes chiefly in terms of autoregressive models of order one. Illustrative numerical examples are given.

Keywords: Autoregressive; processes; Multivariate; stationary; processes; Non-stationary; processes; Periodically; correlated; processes; Reflection; coefficients; Wide; Markov; processes (search for similar items in EconPapers)
Date: 2008
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167-7152(07)00207-6
Full text for ScienceDirect subscribers only

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:eee:stapro:v:78:y:2008:i:2:p:158-164

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

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().