Information theoretic criteria for least-squares trees

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dc.contributor.author Giurcaneanu, Ciprian en
dc.contributor.editor Chen, C-H en
dc.contributor.editor Chan, HP en
dc.coverage.spatial Singapore en
dc.date.accessioned 2016-01-19T01:29:20Z en
dc.date.issued 2015-12 en
dc.identifier.citation IASC-ARS 2015 Book of Abstracts, 2015, pp. 41 - 41 en
dc.identifier.uri http://hdl.handle.net/2292/28032 en
dc.description.abstract Identifying the correct evolutionary tree is an essential and difficult biological problem. It is important to neither over-resolve nor falsely resolve its structure; a problem well-suited to information criteria. Stochastic Complexity (SC) was introduced in [Rissanen(1978)] and since then various forms of it have been derived (see [Rissanen(2012)] for the newest developments of this topic). According to the MDL principle, SC is defined in the context of transmitting the existing data to a hypothesized decoder. The “encoding” is performed by using mathematical models that belong to a pre-defined class, and the model which leads to the shortest code length is deemed to be the most suitable for describing the data [Gr ünwald(2007)]. In this work, we consider SC for assessing phylogenetic trees. To this end, we use SC to encode the parameters and the model (tree) structure. We perform a theoretical comparison of SC with the well- known Bayesian Information Criterion (BIC) and investigate their behavior when the size of the tree→∞and as error → 0. Experiments are conducted with real-world and simulated data in which we compare SC with various forms of BIC, AIC (Akaike Information Criterion) and KIC (Kullback Information Criterion). en
dc.description.uri https://iasc-ars2015.stat.nus.edu.sg/index.php/program/invited-session-organizers en
dc.publisher IASC-ARS en
dc.relation.ispartof 9th Conference of the Asian Regional Section of the IASC (IASC-ARS 2015) en
dc.relation.ispartofseries IASC-ARS 2015 Book of Abstracts en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. en
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.title Information theoretic criteria for least-squares trees en
dc.type Conference Item en
pubs.begin-page 41 en
dc.rights.holder Copyright: IASC-ARS en
pubs.author-url https://iasc-ars2015.stat.nus.edu.sg/images/iasc-ars2015/IASC-ARS2015Booklet.pdf en
pubs.end-page 41 en
pubs.finish-date 2015-12-19 en
pubs.start-date 2015-12-17 en
dc.rights.accessrights http://purl.org/eprint/accessRights/RestrictedAccess en
pubs.subtype Proceedings en
pubs.elements-id 514921 en
pubs.org-id Science en
pubs.org-id Statistics en
pubs.record-created-at-source-date 2015-12-22 en


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