联合广义线性模型中的变量选择
Variable Selection in Joint Generalized Linear Models
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摘要: 在联合广义线性模型中,均值和散度参数都被赋予了广义线性模型的结构,本文主要考虑该模型的变量选择问题. 文章利用扩展拟似然函数,提出了一个适用于联合广义线性模型的新的变量选择准则(EAIC),该准则是Akaike信息准则的推广.论文通过模拟研究和一个实例分析验证了该准则的效果.Abstract: We focus on variable selection in this paper, and propose a variable selection criterion based on the extended quasi-likelihood which is for joint generalized linear models with structured dispersions. The new criterion is an extension of Akaike's information criterion. Its performance is investigated through simulation studies and a real data application.