Probabilistic Disjoint Principal Component Analysis |
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Authors: | Carla Ferrara Francesca Martella Maurizio Vichi |
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Affiliation: | Department of Statistical Sciences, Sapienza University of Rome, Rome, Italy |
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Abstract: | One of the most relevant problems in principal component analysis and factor analysis is the interpretation of the components/factors. In this paper, disjoint principal component analysis model is extended in a maximum-likelihood framework to allow for inference on the model parameters. A coordinate ascent algorithm is proposed to estimate the model parameters. The performance of the methodology is evaluated on simulated and real data sets. |
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Keywords: | Probabilistic model partition of variables maximum-likelihood estimation |
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