Summary Statistics for Endpoint-Conditioned Continuous-Time Markov Chains

DOI10.1239/jap/1324046009zbMath1231.60071OpenAlexW2149464616MaRDI QIDQ3108464

Asger Hobolth, Jens Ledet Jensen

Publication date: 4 January 2012

Published in: Journal of Applied Probability (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1239/jap/1324046009

zbMATH Keywords

uniformizationcontinuous-time Markov chaindwelling timeexpectation maximisation (EM) algorithmtransition number

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Continuous-time Markov processes on general state spaces (60J25) Continuous-time Markov processes on discrete state spaces (60J27)

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Uses Software

• XRate

Cites Work

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• Counting labeled transitions in continuous-time Markov models of evolution
• New Methods for Detecting Lineage-Specific Selection
• The first two moment matrices of the counts for the markovian arrival process
• Computing integrals involving the matrix exponential
• Rounding errors in certain algorithms involving Markov chains
• Nineteen Dubious Ways to Compute the Exponential of a Matrix, Twenty-Five Years Later
• Stochastic Modeling of Scientific Data
• Statistical Inference for Discretely Observed Markov Jump Processes
• Simple derivations of properties of counting processes associated with Markov renewal processes
• Statistical Inference in Evolutionary Models of DNA Sequences via the EM Algorithm

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