Open Access
2010 A generic algorithm for reducing bias in parametric estimation
Ioannis Kosmidis, David Firth
Electron. J. Statist. 4: 1097-1112 (2010). DOI: 10.1214/10-EJS579


A general iterative algorithm is developed for the computation of reduced-bias 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 logit-linear multiple regression model with beta-distributed responses; the results confirm the effectiveness of the new algorithm, and also reveal some important errors in the existing literature on beta regression.


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Ioannis Kosmidis. David Firth. "A generic algorithm for reducing bias in parametric estimation." Electron. J. Statist. 4 1097 - 1112, 2010.


Published: 2010
First available in Project Euclid: 15 October 2010

zbMATH: 1329.62103
MathSciNet: MR2735881
Digital Object Identifier: 10.1214/10-EJS579

Primary: 62F10 , 62F12
Secondary: 62F05

Keywords: Adjusted score , asymptotic bias correction , Beta regression , bias reduction , fisher scoring , prater gasoline data

Rights: Copyright © 2010 The Institute of Mathematical Statistics and the Bernoulli Society

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