Complete moment convergence for partial sums of arrays of rowwise negatively superadditive dependent random variables

Meiqian Chen, Kan Chen, Zijian Wang, Zhengliang Lu and Xuejun Wang

Communications in Statistics - Theory and Methods, 2020, vol. 49, issue 5, 1158-1173

Abstract: In this paper, the complete moment convergence for arrays of rowwise negatively superadditive dependent (NSD, for short) random variables is established. As applications, the complete convergence and the Marcinkiewicz-Zygmund type strong law of large numbers for arrays of rowwise NSD random variables are also obtained. Finally, a numerical simulation is carried out to verify the validity of theoretical results. The results obtained in the paper extend the corresponding ones in the literature.

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2018.1554136 (text/html)
Access to full text is restricted to subscribers.

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:taf:lstaxx:v:49:y:2020:i:5:p:1158-1173

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2018.1554136

Access Statistics for this article

Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe

More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().