A generalized regression model for a binary response
A generalized regression model for a binary response
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DOI：
10.1016/j.spl.2009.09.016
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发表时间：
2010-01-15
影响因子：
0.8
通讯作者：
Agresti, Alan
中科院分区：
文献类型：
--
作者：
Kateri, Maria;Agresti, Alan
鉴于其足够的统计数据，逻辑回归是与 Kullback-Leibler 信息方面的恒定成功概率模型最接近的模型。广义二元模型对于更一般的 phi 散度具有此属性。这些结果可推广到多项式和其他离散数据。 (C) 2009 Elsevier B.V. 保留所有权利。
Logistic regression is the closest model, given its sufficient statistics, to the model of constant success probability in terms of Kullback-Leibler information. A generalized binary model has this property for the more general phi-divergence. These results generalize to multinomial and other discrete data. (C) 2009 Elsevier B.V. All rights reserved.