Numerical Solution of Non-Homogeneous Markov Processes through Uniformization

Numerical algorithms based on uniformization have been proven to be numerically stable and computationally at tractive to compute transient state distributions in ho mogeneous continuous time Markov chains Recently Van Dijk van Dijk formulated uniformization for non homogeneous Markov processes and it is of interest to investigate numerical algorithms based on uniformiza tion for non homogeneous models as well We will in troduce three di erent uniformization based algorithms for non homogeneous Markov processes We implement all three algorithms and use an example of a duplex safety model to compare the algorithms with respect to accuracy memory use and speed Based on these re sults we provide guidelines for the implementation and application of uniformization based algorithms for non homogeneous Markov processes

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