Discrete mixtures in Bayesian networks with hidden variables: a latent time budget example
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 0167-9473Full text not available from this repository.
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|
|Official Date:||28 January 2003|
|Number of Pages:||9|
|Page Range:||pp. 539-547|
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