  Asymptotic properties of Markov Processes, such as steady state probabilities
or hazard rate for absorbing states can be efficiently calculated by means of
linear algebra even for large-scale problems. This paper discusses the methods
for adjusting parameters of the Markov models to account for non-constant
transition rates. In particular, transitions with fixed delays are considered
along with the transitions that follow Weibull and lognormal distributions.
Procedures for both steady-state solutions in the absence of an absorbing
state, and for hazard rates to an absorbing state are provided and demonstrated
on several examples.
