Consistency of deviance-based M estimators

Blackwell Publishing
Publication Type:
Journal Article
Journal of The Royal Statistical Society Series B-methodological, 1987, 49 (3), pp. 326 - 330
Issue Date:
Filename Description Size
Thumbnail2010003475OK.pdf528.04 kB
Adobe PDF
Full metadata record
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.
Please use this identifier to cite or link to this item: