A Procedure for Estimating the Number of Clusters in Logistic Regression Clustering

被引：0
|
作者：
Guoqi Qian
Yuehua Wu
Qing Shao
机构：
[1] The University of Melbourne,Department of Mathematics and Statistics
[2] York University,Department of Mathematics and Statistics
[3] One Health Plaza,Biostatistics and Statistical Reporting
[4] Bldg. 435–4173,undefined
[5] Novartis Pharmaceuticals Corporation,undefined
来源：
Journal of Classification | 2009年 / 26卷
关键词：
Asymptotics; Logistic regression clustering; Model selection; Penalty;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
This paper studies the problem of estimating the number of clusters in the context of logistic regression clustering. The classification likelihood approach is employed to tackle this problem. A model-selection based criterion for selecting the number of logistic curves is proposed and its asymptotic property is also considered. The small sample performance of the proposed criterion is studied by Monto Carlo simulation. In addition, a real data example is presented.
引用
收藏
页码：183 / 199
页数：16
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