Computational information geometry: theory and practice
Abstract
This paper lays the foundations for a unified framework for numerically and computationally applying methods drawn from a range of currently distinct geometrical approaches to statistical modelling. In so doing, it extends information geometry from a manifold based approach to one where the simplex is the fundamental geometrical object, thereby allowing applications to models which do not have a fixed dimension or support. Finally, it starts to build a computational framework which will act as a proxy for the 'space of all distributions' that can be used, in particular, to investigate model selection and model uncertainty. A varied set of substantive running examples is used to illustrate theoretical and practical aspects of the discussion. Further developments are briefly indicated.
Cite
@article{arxiv.1209.1988,
title = {Computational information geometry: theory and practice},
author = {Karim Anaya-Izquierdo and Frank Critchley and Paul Marriott and Paul W. Vos},
journal= {arXiv preprint arXiv:1209.1988},
year = {2012}
}