Kosmidis, I and Firth, D (2011) Multinomial logit bias reduction via the Poisson log-linear model. BIOMETRIKA , 98 (3) 755 - 759. 10.1093/biomet/asr026.
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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.
| Type: | Article |
|---|---|
| Title: | Multinomial logit bias reduction via the Poisson log-linear model |
| DOI: | 10.1093/biomet/asr026 |
| Keywords: | Jeffreys prior, Leverage, Logistic linear regression, Poisson trick, LOGISTIC-REGRESSION, MAXIMUM-LIKELIHOOD |
| UCL classification: | UCL > School of BEAMS > Faculty of Maths and Physical Sciences > Statistical Science |
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