Constructing processes with prescribed mixing coefficients
Kontorovich, Leonid (Aryeh)
Statistics & Probability Letters, 2008, vol. 78, issue 17, 2910-2915
Abstract:
The rate at which dependencies between future and past observations decay in a random process may be quantified in terms of mixing coefficients. The latter in turn appear in strong laws of large numbers and concentration of measure inequalities for dependent random variables. Questions regarding what rates are possible for various notions of mixing have been posed since the 1960's, and have important implications for some open problems in the theory of strong mixing conditions. This paper deals with [eta]-mixing, a notion defined in [Kontorovich, Leonid, Ramanan, Kavita, 2008. Concentration inequalities for dependent random variables via the martingale method. Ann. Probab. (in press)], which is closely related to [phi]-mixing. We show that there exist measures on finite sequences with essentially arbitrary [eta]-mixing coefficients, as well as processes with arbitrarily slow mixing rates.
Date: 2008
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167-7152(08)00235-6
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:17:p:2910-2915
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 ().