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A generic algorithm for reducing bias in parametric estimation
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Kosmidis, Ioannis and Firth, David. (2010) A generic algorithm for reducing bias in parametric estimation. Electronic Journal of Statistics, Vol.4 . pp. 10971112. ISSN 19357524

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Official URL: http://dx.doi.org/10.1214/10EJS579
Abstract
A general iterative algorithm is developed for the computation of reducedbias parameter estimates in regular statistical models through adjustments to the score function. The algorithm unifies and provides appealing new interpretation for iterative methods that have been published previously for some specific model classes. The new algorithm can usefully be viewed as a series of iterative bias corrections, thus facilitating the adjusted score approach to bias reduction in any model for which the first order bias of the maximum likelihood estimator has already been derived. The method is tested by application to a logitlinear multiple regression model with betadistributed responses; the results confirm the effectiveness of the new algorithm, and also reveal some important errors in the existing literature on beta regression.
Item Type:  Journal Article 

Subjects:  Q Science > QA Mathematics 
Divisions:  Faculty of Science > Statistics 
Library of Congress Subject Headings (LCSH):  Parameter estimation, Mathematical models 
Journal or Publication Title:  Electronic Journal of Statistics 
Publisher:  Institute of Mathematical Statistics 
ISSN:  19357524 
Date:  2010 
Volume:  Vol.4 
Page Range:  pp. 10971112 
Identification Number:  10.1214/10EJS579 
Status:  Peer Reviewed 
Access rights to Published version:  Open Access 
Funder:  Engineering and Physical Sciences Research Council (EPSRC) 
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URI:  http://wrap.warwick.ac.uk/id/eprint/4341 
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