A Computational Method for Analyzing Continuous-Time Markov Reward Chains

This paper investigates continuous-time Markov reward chains, where the intensity (or velocity) of reward depends on the current state of the Markov chain. If the chain is in the i-th state, the reward intensity equals c_i>0. The goal of this paper is to compute the distribution of reward at a given time t. The embedded chain method is used at the moments of state transition.