Consistency of deviance-based M estimators

Lenth, RV; Green, PJ

Consistency of deviance-based M estimators

Lenth, RV Green, PJ

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Publisher:: Blackwell Publishing
Publication Type:: Journal Article
Citation:: Journal of The Royal Statistical Society Series B-methodological, 1987, 49 (3), pp. 326 - 330
Issue Date:: 1987-01

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Field	Value	Language
dc.contributor.author	Lenth, RV	en_US
dc.contributor.author	Green, PJ https://orcid.org/0000-0002-4367-4756	en_US
dc.date.issued	1987-01	en_US
dc.identifier.citation	Journal of The Royal Statistical Society Series B-methodological, 1987, 49 (3), pp. 326 - 330	en_US
dc.identifier.issn	1369-7412	en_US
dc.identifier.uri	http://hdl.handle.net/10453/14546
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.	en_US
dc.publisher	Blackwell Publishing	en_US
dc.relation.ispartof	Journal of The Royal Statistical Society Series B-methodological	en_US
dc.subject.classification	Statistics & Probability	en_US
dc.title	Consistency of deviance-based M estimators	en_US
dc.type	Journal Article
utslib.citation.volume	3	en_US
utslib.citation.volume	49	en_US
utslib.for	0104 Statistics	en_US
utslib.for	0102 Applied Mathematics	en_US
utslib.for	1403 Econometrics	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
utslib.copyright.status	closed_access
pubs.consider-herdc	false	en_US
pubs.issue	3	en_US
pubs.volume	49	en_US

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.

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http://hdl.handle.net/10453/14546