Multinomial logit bias reduction via the Poisson log-linear model

Ioannis Kosmidis and David Firth

Biometrika, 2011, vol. 98, issue 3, 755-759

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. Copyright 2011, Oxford University Press.

Date: 2011
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