Please use this identifier to cite or link to this item: https://doi.org/10.1239/jap/1245676102
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dc.titleSimilar states in continuous-time Markov chains
dc.contributor.authorYap, V.B.
dc.date.accessioned2014-10-28T05:15:11Z
dc.date.available2014-10-28T05:15:11Z
dc.date.issued2009-06
dc.identifier.citationYap, V.B. (2009-06). Similar states in continuous-time Markov chains. Journal of Applied Probability 46 (2) : 497-506. ScholarBank@NUS Repository. https://doi.org/10.1239/jap/1245676102
dc.identifier.issn00219002
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/105364
dc.description.abstractIn a homogeneous continuous-time Markov chain on a finite state space, two states that jump to every other state with the same rate are called similar. By partitioning states into similarity classes, the algebraic derivation of the transition matrix can be simplified, using hidden holding times and lumped Markov chains. When the rate matrix is reversible, the transition matrix is explicitly related in an intuitive way to that of the lumped chain. The theory provides a unified derivation for a whole range of useful DNA base substitution models, and a number of amino acid substitution models. © Applied Probability Trust 2009.
dc.sourceScopus
dc.subjectHolding time
dc.subjectLumped Markov chain
dc.subjectReversibility
dc.subjectUniformisation
dc.typeArticle
dc.contributor.departmentSTATISTICS & APPLIED PROBABILITY
dc.description.doi10.1239/jap/1245676102
dc.description.sourcetitleJournal of Applied Probability
dc.description.volume46
dc.description.issue2
dc.description.page497-506
dc.identifier.isiut000267854000014
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