  Flowgraph models provide an alternative approach in modeling a multi-state
stochastic process. One of the most widely used stochastic processes that have
many real-world applications especially in actuarial models is the Markov jump
process or continuous- time Markov chain. However, finding waiting time
distributions between any two states in a Markov jump process can be very
difficult. Flowgraph analysis for Markov jump process comprises of modeling the
possible states of the process, the interstates waiting time distribution, and
working on the moment generating function domain to obtain the total waiting
time distribution in form of density or survival function. This paper gives the
theory and computational method of flowgraph analysis, uses it in Markov
process problems, and compares the traditional Markov process construction
method with the flowgraph method to demonstrate the convenience and
practicality of flowgraph analysis.
