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Bayesian model learning based on a parallel MCMC strategy
Linköping University, The Institute of Technology. Linköping University, Department of Mathematics, Mathematical Statistics .
Institutionen för matematik och statistik Helsingfors universitet.
Insitution för matematik och statistik Helsingfors universitet.
2006 (English)In: Statistics and computing, ISSN 0960-3174, E-ISSN 1573-1375, Vol. 16, no 2, 355-362 p.Article in journal (Refereed) Published
Abstract [en]

  Interacting parallell Markov chains are shown to converge to a maximum of the posterior on a set of partitions of a finite set of discrete data. This is demonstrated on an example of population genetics data.

Place, publisher, year, edition, pages
2006. Vol. 16, no 2, 355-362 p.
Keyword [en]
classification, learning
National Category
Mathematics
Identifiers
URN: urn:nbn:se:liu:diva-35479DOI: 10.1007/s11222-006-9391-yLocal ID: 27026OAI: oai:DiVA.org:liu-35479DiVA: diva2:256327
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2017-12-13

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Publisher's full texthttp://springerlink.metapress.com/content/u710k5v3783j/?p=123b2a7d3df84e569f2ae5efd4081d85&pi=0

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Koski, Timo

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