Computational information geometry in statistics: theory and practice

Critchley, Frank and Marriott, Paul (2014). Computational information geometry in statistics: theory and practice. Entropy, 16(5) pp. 2454–2471.

DOI: https://doi.org/10.3390/e16052454

Abstract

A broad view of the nature and potential of computational information geometry in statistics is offered. This new area suitably extends the manifold-based approach of classical information geometry to a simplicial setting, in order to obtain an operational universal model space. Additional underlying theory and illustrative real examples are presented. In the infinite-dimensional case, challenges inherent in this ambitious overall agenda are highlighted and promising new methodologies indicated.

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