Multinomial logit bias reduction via the Poisson log-linear model

• 成果类型: Article
• 署名作者: Kosmidis, Ioannis; Firth, David
• 署名单位: University of London; University College London; University of Warwick
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/asr026
• 发表日期: 2011
• 页码: 755759
• 关键词: logistic-regression; maximum-likelihood

摘要

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.