2012/09/10 by Karim Anaya‐Izquierdo, Frank Critchley, Anaya-Izquierdo, Karim +5
Computer Science · Mathematics · #Advanced Statistical Methods and Models #Bayesian Modeling and Causal Inference #Computation (stat.CO) #FOS: Computer and information sciences #FOS: Mathematics #Rough Sets and Fuzzy Logic #Statistics Theory (math.ST)
paper · pdf · doi:10.48550/arxiv.1209.1988
openalex publication_date 2012/09/10 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.