Seriation in paleontological data using Markov Chain Monte Carlo methods

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dc.contributor University of Helsinki, Helsinki University of Technology en
dc.contributor University of Helsinki, Geologian ja paleontologian osasto (-2009) en
dc.contributor.author Puolamäki, Kai
dc.contributor.author Fortelius, Mikael
dc.contributor.author Mannila, Heikki
dc.date.accessioned 2016-06-09T13:53:02Z
dc.date.available 2016-06-09T13:53:02Z
dc.date.issued 2006
dc.identifier.citation Puolamäki , K , Fortelius , M & Mannila , H 2006 , ' Seriation in paleontological data using Markov Chain Monte Carlo methods ' , PLoS Computational Biology , vol. 2 , no. 2 , pp. 1-9 . https://doi.org/10.1371/journal.pcbi.0020006 en
dc.identifier.issn 1553-734X
dc.identifier.other PURE: 607768
dc.identifier.other PURE UUID: f321ae50-4ff8-46a2-930a-d1aeda7b01ee
dc.identifier.other dawa_publication: 155866
dc.identifier.other WOS: 000239493500002
dc.identifier.other Scopus: 33645797854
dc.identifier.other ORCID: /0000-0002-4851-783X/work/30278264
dc.identifier.other ORCID: /0000-0003-1819-1047/work/53186315
dc.identifier.uri http://hdl.handle.net/10138/163548
dc.description.abstract Given a collection of fossil sites with data about the taxa that occur in each site, the task in biochronology is to find good estimates for the ages or ordering of sites. We describe a full probabilistic model for fossil data. The parameters of the model are natural: the ordering of the sites, the origination and extinction times for each taxon, and the probabilities of different types of errors. We show that the posterior distributions of these parameters can be estimated reliably by using Markov chain Monte Carlo techniques. The posterior distributions of the model parameters can be used to answer many different questions about the data, including seriation (finding the best ordering of the sites) and outlier detection. We demonstrate the usefulness of the model and estimation method on synthetic data and on real data on large late Cenozoic mammals. As an example, for the sites with large number of occurrences of common genera, our methods give orderings, whose correlation with geochronologic ages is 0.95. sv
dc.format.extent 9
dc.language.iso eng
dc.relation.ispartof PLoS Computational Biology
dc.rights en
dc.subject 113 Computer and information sciences en
dc.title Seriation in paleontological data using Markov Chain Monte Carlo methods en
dc.type Article
dc.description.version Peer reviewed
dc.identifier.doi https://doi.org/10.1371/journal.pcbi.0020006
dc.type.uri info:eu-repo/semantics/other
dc.type.uri info:eu-repo/semantics/publishedVersion
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