Multistate Markov Models and Structural Properties of the Transition-Rate Matrix
Giuseppe Cafaro, Francesco Corsi, Francesco Vacca
Abstract
Giuseppe Cafaro, Francesco Corsi, Francesco Vacca
Abstract
This paper explains how to use Markov models for evaluating the availability and reliability of a system when the transition rates of each component depend on the state of the system. To this purpose, the structural properties of the system transition-rate matrix, obtained by the Kronecker sum of transition rate matrices of the components, are analyzed. As a result, an efficient use of the Markov model is possible by mapping the transition rates of the single components into the elements of the system transition-rate matrix. The potential of parallel computers can facilitate this approach, giving renewed interest to the Markov method for complex systems.
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This paper explains how to use Markov models for evaluating the availability and reliability of a system when the transition rates of each component depend on the state of the system. To this purpose, the structural properties of the system transition-rate matrix, obtained by the Kronecker sum of transition rate matrices of the components, are analyzed. As a result, an efficient use of the Markov model is possible by mapping the transition rates of the single components into the elements of the system transition-rate matrix. The potential of parallel computers can facilitate this approach, giving renewed interest to the Markov method for complex systems.
Key concepts: Markov chain, Transition rate matrix, Stochastic matrix, Markov model, Markov process, Continuous-time Markov chain, Markov kernel, Kronecker delta