Entropy 2014, 16(5), 2454-2471; doi:10.3390/e16052454
Article

Computational Information Geometry in Statistics: Theory and Practice

1email and 2,* email
Received: 27 March 2014; in revised form: 25 April 2014 / Accepted: 29 April 2014 / Published: 2 May 2014
(This article belongs to the Special Issue Information Geometry)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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.
Keywords: information geometry; computational geometry; statistical foundations
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MDPI and ACS Style

Critchley, F.; Marriott, P. Computational Information Geometry in Statistics: Theory and Practice. Entropy 2014, 16, 2454-2471.

AMA Style

Critchley F, Marriott P. Computational Information Geometry in Statistics: Theory and Practice. Entropy. 2014; 16(5):2454-2471.

Chicago/Turabian Style

Critchley, Frank; Marriott, Paul. 2014. "Computational Information Geometry in Statistics: Theory and Practice." Entropy 16, no. 5: 2454-2471.

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