Generating Markov-Chain Transitions Quickly: II
Copyright policy )Generating Markov-Chain Transitions Quickly: II
A predecessor to this paper gives a way to generate transitions in continuous-time Markov chains. It is fast when a “similarity” condition holds. Exploiting a balanced binary search tree, we reduce the computational complexity of that method. INFORMS Journal on Computing, ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.
- University of Colorado Denver United States
Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.), computational complexity, Jackson-like queueing networks, Monte Carlo methods, way to generate transitions in continuous-time Markov chains
Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.), computational complexity, Jackson-like queueing networks, Monte Carlo methods, way to generate transitions in continuous-time Markov chains
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