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Discrete mixtures in Bayesian networks with hidden variables: a latent time budget example
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UNSPECIFIED (2003) Discrete mixtures in Bayesian networks with hidden variables: a latent time budget example. COMPUTATIONAL STATISTICS & DATA ANALYSIS, 41 (3-4). pp. 539-547. ISSN 0167-9473.
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Abstract
The existing methods of analysis applicable to time budget data are summarised. Latent budget models, a subclass of general reduced rank models for two-way contingency tables, are most appropriate as they view each of the observed conditional distributions of interest as a mixture of a small number of conditional distributions involving a hidden variable. However, they suffer from unusually complex unidentifiability problems which can cause standard estimation methods to perform badly and/or be misleading. Recent advances in estimation methods for this type of mixture model which address the unidentifiability issues are reported and demonstrated. (C) 2002 Published by Elsevier Science B.V.
Item Type: | Journal Article | ||||
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Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software Q Science > QA Mathematics |
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Journal or Publication Title: | COMPUTATIONAL STATISTICS & DATA ANALYSIS | ||||
Publisher: | ELSEVIER SCIENCE BV | ||||
ISSN: | 0167-9473 | ||||
Official Date: | 28 January 2003 | ||||
Dates: |
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Volume: | 41 | ||||
Number: | 3-4 | ||||
Number of Pages: | 9 | ||||
Page Range: | pp. 539-547 | ||||
Publication Status: | Published |
Data sourced from Thomson Reuters' Web of Knowledge
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