 |
|
 | Publication |  |
| 2007 | McLachlan, G. J., Bean, R. W. and Jones, L. B. T. (2007) Extension of the Mixture of Factor Analyzers Model to Incorporate the Multivariate t-Distribution. Computational Statistics & Data Analysis, 51 11: 5327-5338. |
|
Mixtures of factor analyzers enable model-based density estimation to be undertaken for high-dimensional data, where the number of observations n is small relative to their dimension p. However, this approach is sensitive to outliers as it is based on a mixture model in which the multivariate normal family of distributions is assumed for the component error and factor distributions. An extension to mixtures of t-factor analyzers is considered, whereby the multivariate t-family is adopted for the component error and factor distributions. An EM-based algorithm is developed for the fitting of mixtures of t-factor analyzers. lts application is demonstrated in the clustering of some microarray gene-expression data. (C) 2006 Elsevier B.V. All rights reserved.
| |  Professor Geoff McLachlan | | eSpace Record: |
http://espace.library.uq.edu.au/view/UQ:134950
| | | | | Links: | Link to full text |
| Keywords: | Computer Science, Interdisciplinary Applications | | |
<< Back to Publication List
|
|
» Contacts
