Computational information geometry in statistics: mixture modelling

Anaya Izquierdo, Karim; Critchley, Frank; Marriott, Paul and Vos, Paul (2013). Computational information geometry in statistics: mixture modelling. In: Geometric Science of Information, 28-30 Aug 2013, École des Mines, Paris.

DOI: https://doi.org/10.1007/978-3-642-40020-9

URL: http://www.see.asso.fr/node/4339

Abstract

This paper applies the tools of computation information geometry [3] – in particular, high dimensional extended multinomial families as proxies for the ‘space of all distributions’ – in the inferentially demanding area of statistical mixture modelling. A range of resultant benefits are noted.

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