A Probabilistic Clustering Model for Variables of Mixed Type

A Probabilistic Clustering Model for Variables of Mixed Type This paper develops a probabilistic clustering model for mixeddata. The model allows analysis of variables of mixed type: thevariables may be nominal, ordinal and/or quantitative. The modelcontains the well-known models of latent class analysis as submodels.As in latent class analysis, local independence of the variables isassumed. The parameters of the model are estimated by the EMalgorithm. Test statistics and goodness-of-fit measures are proposedfor model selection. Two artificial data sets show the usefulness ofthese tests. An empirical example completes the presentation. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quality & Quantity Springer Journals

A Probabilistic Clustering Model for Variables of Mixed Type

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Publisher
Kluwer Academic Publishers
Copyright
Copyright © 2000 by Kluwer Academic Publishers
Subject
Social Sciences; Methodology of the Social Sciences; Social Sciences, general
ISSN
0033-5177
eISSN
1573-7845
D.O.I.
10.1023/A:1004759101388
Publisher site
See Article on Publisher Site

Abstract

This paper develops a probabilistic clustering model for mixeddata. The model allows analysis of variables of mixed type: thevariables may be nominal, ordinal and/or quantitative. The modelcontains the well-known models of latent class analysis as submodels.As in latent class analysis, local independence of the variables isassumed. The parameters of the model are estimated by the EMalgorithm. Test statistics and goodness-of-fit measures are proposedfor model selection. Two artificial data sets show the usefulness ofthese tests. An empirical example completes the presentation.

Journal

Quality & QuantitySpringer Journals

Published: Oct 16, 2004

References

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