Semiparametric mixture models and repeated measures: the multinomial cut point model

被引:16
作者
Cruz-Medina, IR
Hettmansperger, TP
Thomas, H
机构
[1] Penn State Univ, Dept Stat, Eberly Coll Sci, University Pk, PA 16802 USA
[2] Inst Tecnol Sonora, Obregon, Sonora, Mexico
关键词
EM algorithm; finite mixtures; multinomial likelihood; nonparametric estimation;
D O I
10.1111/j.1467-9876.2004.05203.x
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 [统计学]; 070103 [概率论与数理统计]; 0714 [统计学];
摘要
Suppose that we have m repeated measures on each subject, and we model the observation vectors with a finite mixture model. We further assume that the repeated measures are conditionally independent. We present methods to estimate the shape of the component distributions along with various features of the component distributions such as the medians, means and variances. We make no distributional assumptions on the components; indeed, we allow different shapes for different components.
引用
收藏
页码:463 / 474
页数:12
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