论文标题
一般对数线性模型中的最大似然估计
On the maximum likelihood estimation in general log-linear models
论文作者
论文摘要
通过非负整数设计矩阵指定的一般日志线性模型具有潜在的应用程序，尽管使用没有真正总体效应的模型，也就是说，不能重新聚集以包括标准化常数的模型，但仍然很少见。没有整体效果的对数线性模型在实践中自然出现，并且可以与具有整体效果的模型相似。提出了在此类模型下进行MLE计算的新型迭代缩放程序，并证明了其收敛性。使用最近一项临床研究的数据来说明结果。
General log-linear models specified by non-negative integer design matrices have a potentially wide range of applications, although using models without the genuine overall effect, that is, ones which cannot be reparameterized to include a normalizing constant, is still rare. The log-linear models without the overall effect arise naturally in practice, and can be handled in a similar manner to models with the overall effect. A novel iterative scaling procedure for the MLE computation under such models is proposed, and its convergence is proved. The results are illustrated using data from a recent clinical study.
