Consistency of deviance-based M estimators

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Show simple item record Lenth, RV Green, PJ 2012-02-02T04:36:22Z 1987-01
dc.identifier.citation Journal of The Royal Statistical Society Series B-methodological, 1987, 49 (3), pp. 326 - 330
dc.identifier.issn 1369-7412
dc.identifier.other C1UNSUBMIT en_US
dc.description.abstract In a general estimation problem, the deviance function generates statistics that are similar to squared standardized residuals. A deviance-based M estimator (DBME) is defined as an adaptively weighted maximum-likelihood estimator, where the weights depend upon the deviances. In both a single-parameter and a regression setting, we give some general conditions under which a DMBE is consistent. For a suitable weighting scheme, these conditions are satisfied in many continuous Cramer-Rao-regular families and in related linear or nonlinear regression cases. The conditions fail (and the estimator is inconsistent) in most discrete families.
dc.format Esha Dutt
dc.publisher Blackwell Publishing
dc.title Consistency of deviance-based M estimators
dc.type Journal Article
dc.description.version Published
dc.parent Journal of The Royal Statistical Society Series B-methodological
dc.journal.volume 3
dc.journal.volume 49
dc.journal.number 3 en_US
dc.publocation United Kingdom en_US
dc.identifier.startpage 326 en_US
dc.identifier.endpage 330 en_US SCI.Faculty of Science en_US
dc.conference Verified OK en_US
dc.for 0104 Statistics
dc.personcode 112334
dc.percentage 100 en_US Statistics en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom en_US en_US
dc.location.activity en_US
dc.description.keywords NA
pubs.embargo.period Not known
pubs.organisational-group /University of Technology Sydney
pubs.organisational-group /University of Technology Sydney/Faculty of Science
utslib.copyright.status Closed Access 2015-04-15 12:17:09.805752+10
pubs.consider-herdc false
utslib.collection.history Closed (ID: 3)
utslib.collection.history School of Mathematical Sciences (ID: 340)
utslib.collection.history School of Mathematical Sciences (ID: 340)

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