Multinomial logit bias reduction via the Poisson log-linear model

Kosmidis, I. and Firth, D. (2011) Multinomial logit bias reduction via the Poisson log-linear model. Biometrika, 98 (3). pp. 755-759. ISSN 0006-3444

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Abstract

For the parameters of a multinomial logistic regression, it is shown how to obtain the bias-reducing penalized maximum likelihood estimator by using the equivalent Poisson log-linear model. The calculation needed is not simply an application of the Jeffreys prior penalty to the Poisson model. The development allows a simple and computationally efficient implementation of the reduced-bias estimator, using standard software for generalized linear models.

Item Type: Article
Subjects: 5. Quantitative Data Handling and Data Analysis > 5.5 Regression Methods
Depositing User: L-W-S user
Date Deposited: 20 Feb 2012 15:09
Last Modified: 14 Jul 2021 13:55
URI: https://eprints.ncrm.ac.uk/id/eprint/2081

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