Computational information geometry in statistics: mixture modelling

Karim Anaya-Izquierdo, Frank Critchley, Paul Marriott, Paul Vos

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

This paper applies the tools of computation information geometry – 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.
Original languageEnglish
Title of host publicationGeometric Science of Information
Subtitle of host publicationFirst International Conference, GSI 2013, Paris, France, August 28-30, 2013. Proceedings
EditorsFrank Nielsen, Frédéric Barbaresco
Place of PublicationBerlin, Germany
PublisherSpringer
Pages319-326
Number of pages8
VolumeIX
ISBN (Print)9783642400193
DOIs
Publication statusPublished - 2013

Publication series

NameLecture Notes in Computer Science
Volume8085

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