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Article: The strong law of large numbers for extended negatively dependent random variables

TitleThe strong law of large numbers for extended negatively dependent random variables
Authors
KeywordsAsymptotics
Borel-Cantelli lemma
Lower/upper extended negative dependence
Renewal counting process
Strong law of large numbers
Truncation
Issue Date2010
PublisherApplied Probability Trust. The Journal's web site is located at http://www.shef.ac.uk/uni/companies/apt/ap.html
Citation
Journal Of Applied Probability, 2010, v. 47 n. 4, p. 908-922 How to Cite?
AbstractA sequence of random variables is said to be extended negatively dependent (END) if the tails of its finite-dimensional distributions in the lower-left and upper-right corners are dominated by a multiple of the tails of the corresponding finite-dimensional distributions of a sequence of independent random variables with the same marginal distributions. The goal of this paper is to establish the strong law of large numbers for a sequence of END and identically distributed random variables. In doing so we derive some new inequalities of large deviation type for the sums of END and identically distributed random variables being suitably truncated. We also show applications of our main result to risk theory and renewal theory. © 2010 Applied Probability Trust.
Persistent Identifierhttp://hdl.handle.net/10722/142513
ISSN
2015 Impact Factor: 0.665
2015 SCImago Journal Rankings: 0.742
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorChen, Yen_HK
dc.contributor.authorChen, Aen_HK
dc.contributor.authorNg, KWen_HK
dc.date.accessioned2011-10-28T02:50:03Z-
dc.date.available2011-10-28T02:50:03Z-
dc.date.issued2010en_HK
dc.identifier.citationJournal Of Applied Probability, 2010, v. 47 n. 4, p. 908-922en_HK
dc.identifier.issn0021-9002en_HK
dc.identifier.urihttp://hdl.handle.net/10722/142513-
dc.description.abstractA sequence of random variables is said to be extended negatively dependent (END) if the tails of its finite-dimensional distributions in the lower-left and upper-right corners are dominated by a multiple of the tails of the corresponding finite-dimensional distributions of a sequence of independent random variables with the same marginal distributions. The goal of this paper is to establish the strong law of large numbers for a sequence of END and identically distributed random variables. In doing so we derive some new inequalities of large deviation type for the sums of END and identically distributed random variables being suitably truncated. We also show applications of our main result to risk theory and renewal theory. © 2010 Applied Probability Trust.en_HK
dc.languageengen_US
dc.publisherApplied Probability Trust. The Journal's web site is located at http://www.shef.ac.uk/uni/companies/apt/ap.htmlen_HK
dc.relation.ispartofJournal of Applied Probabilityen_HK
dc.rightsJournal of Applied Probability. Copyright © Applied Probability Trust.en_US
dc.subjectAsymptoticsen_HK
dc.subjectBorel-Cantelli lemmaen_HK
dc.subjectLower/upper extended negative dependenceen_HK
dc.subjectRenewal counting processen_HK
dc.subjectStrong law of large numbersen_HK
dc.subjectTruncationen_HK
dc.titleThe strong law of large numbers for extended negatively dependent random variablesen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0021-9002&volume=47&issue=4&spage=908&epage=922&date=2010&atitle=The+strong+law+of+large+numbers+for+extended+negatively+dependent+random+variables-
dc.identifier.emailNg, KW: kaing@hkucc.hku.hken_HK
dc.identifier.authorityNg, KW=rp00765en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1239/jap/1294170508en_HK
dc.identifier.scopuseid_2-s2.0-79958769547en_HK
dc.identifier.hkuros184663en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-79958769547&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume47en_HK
dc.identifier.issue4en_HK
dc.identifier.spage908en_HK
dc.identifier.epage922en_HK
dc.identifier.isiWOS:000286958100002-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridChen, Y=42261457500en_HK
dc.identifier.scopusauthoridChen, A=7403392194en_HK
dc.identifier.scopusauthoridNg, KW=7403178774en_HK

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