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|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|
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|Links: ||Link to full text|
|Keywords: ||Computer Science, Interdisciplinary Applications|