Latent class models for mixed variables with applications in archaeometry
Latent class models for mixed variables with applications in archaeometry
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DOI：
10.1016/j.csda.2004.03.001
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发表时间：
2005-03-01
影响因子：
1.8
通讯作者：
Papageorgiou, I
中科院分区：
文献类型：
--
作者：
Moustaki, I;Papageorgiou, I
潜在类别模型在社会科学中用于根据对一组观察指标的响应将个体或对象分类为不同的组/类别。混合二进制和度量变量的潜在类模型（Br. J. Math. Statist. Psych. 49 (1996) 313）被扩展以适应任何类型的数据（包括序数和名义数据），并讨论了它在考古学中将考古发现/物体分类的用途。所提出的模型是使用 EM 算法的最大似然估计来估计的。考古发现的两个数据集用于说明该方法。 (C) 2004 Elsevier B.V. 保留所有权利。
Latent class models are used in social sciences for classifying individuals or objects into distinct groups/classes based on responses to a set of observed indicators. The latent class model for mixed binary and metric variables (Br. J. Math. Statist. Psych. 49 (1996) 313) is extended to accommodate any type of data (including ordinal and nominal) and its use in Archaeometry for classifying archaeological findings/objects into groups is discussed. The models proposed are estimated using a full maximum like-lihood with the EM algorithm. Two data sets from archaeological findings are used to illustrate the methodology. (C) 2004 Elsevier B.V. All rights reserved.