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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
Full text not available from this repository.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 |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software Q Science > QA Mathematics |
| Journal or Publication Title: | COMPUTATIONAL STATISTICS & DATA ANALYSIS |
| Publisher: | ELSEVIER SCIENCE BV |
| ISSN: | 0167-9473 |
| Date: | 28 January 2003 |
| Volume: | 41 |
| Number: | 3-4 |
| Number of Pages: | 9 |
| Page Range: | pp. 539-547 |
| Publication Status: | Published |
| URI: | http://wrap.warwick.ac.uk/id/eprint/10087 |
Data sourced from Thomson Reuters' Web of Knowledge
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