Bootstrapping latent class models

被引：2
|
作者：
Dias, JG [1 ]
机构：
[1] ISCTE, Dept Quantitat Methods, P-1649026 Lisbon, Portugal
来源：
Classification - the Ubiquitous Challenge | 2005年
关键词：
D O I：
10.1007/3-540-28084-7_11
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper deals with improved measures of statistical accuracy for parameter estimates of latent class models. It introduces more precise confidence intervals for the parameters of this model, based on parametric and nonparametric bootstrap. Moreover, the label-switching problem is discussed and a solution to handle it introduced. The results are illustrated using a well-known dataset.
引用
收藏
页码：121 / 128
页数：8
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