An estimator of the mutual information based on a criterion for independence
Computational Statistics & Data Analysis
Estimation of the information by an adaptive partitioning of the observation space
IEEE Transactions on Information Theory
On convergence of information contained in quantized observations
IEEE Transactions on Information Theory
On functionals satisfying a data-processing theorem
IEEE Transactions on Information Theory
On Divergences and Informations in Statistics and Information Theory
IEEE Transactions on Information Theory
Asymptotically Sufficient Partitions and Quantizations
IEEE Transactions on Information Theory
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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.