Next Article in Journal / Special Issue
F-Geometry and Amari’s α-Geometry on a Statistical Manifold
Previous Article in Journal
Optimization of Biomass-Fuelled Combined Cooling, Heating and Power (CCHP) Systems Integrated with Subcritical or Transcritical Organic Rankine Cycles (ORCs)
Previous Article in Special Issue
Information Geometry of Positive Measures and Positive-Definite Matrices: Decomposable Dually Flat Structure
Article Menu

Export Article

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

Computational Information Geometry in Statistics: Theory and Practice

1
Department of Mathematics and Statistics, The Open University, Walton Hall, Milton Keynes,Buckinghamshire MK7 6AA, UK
2
Department of Statistics and Actuarial Science, University of Waterloo, 200 University Avenue West, Waterloo, ON N2L 3G1, Canada
*
Author to whom correspondence should be addressed.
Received: 27 March 2014 / Revised: 25 April 2014 / Accepted: 29 April 2014 / Published: 2 May 2014
(This article belongs to the Special Issue Information Geometry)
View Full-Text   |   Download PDF [735 KB, uploaded 24 February 2015]   |  

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 information geometry; computational geometry; statistical foundations
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

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

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Entropy EISSN 1099-4300 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top