Modelling high-dimensional data by mixtures of factor analyzers
@article{McLachlan2003ModellingHD, title={Modelling high-dimensional data by mixtures of factor analyzers}, author={G. McLachlan and D. Peel and Richard Bean}, journal={Comput. Stat. Data Anal.}, year={2003}, volume={41}, pages={379-388} }
We focus on mixtures of factor analyzers from the perspective of a method for model-based density estimation from high-dimensional data, and hence for the clustering of such data. This approach enables a normal mixture model to be fitted to a sample of n data points of dimension p, where p is large relative to n. The number of free parameters is controlled through the dimension of the latent factor space. By working in this reduced space, it allows a model for each component-covariance matrix… CONTINUE READING
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