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Optimal Quantization of the Support of a Continuous Multivariate Distribution based on Mutual Information

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Abstract

Based on the notion of mutual information between the components of a random vector, we construct, for data reduction reasons, an optimal quantization of the support of its probability measure. More precisely, we propose a simultaneous discretization of the whole set of the components of the random vector which takes into account, as much as possible, the stochastic dependence between them. Examples are presented.

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Correspondence to Bernard Colin.

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The authors are grateful to anonymous referees for a careful reading and detailed revision of the original manuscript. Their valuable comments contributed to improve the presentation of our work.

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Colin, B., Dubeau, F., Khreibani, H. et al. Optimal Quantization of the Support of a Continuous Multivariate Distribution based on Mutual Information. J Classif 30, 453–473 (2013). https://doi.org/10.1007/s00357-013-9127-6

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  • DOI: https://doi.org/10.1007/s00357-013-9127-6

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