View Item 

Show simple item record

On the law of large numbers for the bootstrap mean
dc.contributor.authorCsorgo, Sandoren_US
dc.date.accessioned2006-04-10T15:13:35Z
dc.date.available2006-04-10T15:13:35Z
dc.date.issued1992-05-04en_US
dc.identifier.citationCsorgo, Sandor (1992/05/04)."On the law of large numbers for the bootstrap mean." Statistics &amp; Probability Letters 14(1): 1-7. <http://hdl.handle.net/2027.42/30055>en_US
dc.identifier.urihttp://www.sciencedirect.com/science/article/B6V1D-45DHJ51-15/2/3987568ca5a51296866b46c6bb142a41en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/30055
dc.description.abstractDirect and elementary proofs are given for weak and strong laws of large numbers for bootstrap sample means under minimal moment conditions. Concerning the required rate of divergence of the bootstrap sample size, the strong laws obtained improve on those of Athreya (1983).Ams 1980 Subject Classifications: Primary 60F15; Secondary 62G05en_US
dc.format.extent467819 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherElsevieren_US
dc.titleOn the law of large numbers for the bootstrap meanen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelStatistics and Numeric Dataen_US
dc.subject.hlbsecondlevelMathematicsen_US
dc.subject.hlbtoplevelSocial Sciencesen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Statistics, University of Michigan, Ann Arbor, MI 48109-1027, USAen_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/30055/1/0000423.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1016/0167-7152(92)90203-Hen_US
dc.identifier.sourceStatistics &amp; Probability Lettersen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


Files in this item

Name:
0000423.pdf
Size:
456.8KB
Format:
PDF
View/Open

Show simple item record

Remediation of Harmful Language

The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.

Accessibility

If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.