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  1. Let $X=(X_{t},t \in T)$ be a non-homogeneous, continuous time Markov process with a finite state space S={1,...,K}.

  2. Let $\alpha_{i,j}(t)$ be the hazard rates of some $\varGamma$-distributed random variables.

$\textbf{Question}:$ How can I simulate random paths of the Markov process with a transition intensity matrix which is built with the above hazard rates $\alpha_{i,j}(t)$?

For example: S={1,2,3,4} with given $\alpha_{i,j}(t), i,j \in S$

Any idea is greatly appreciated, with best regards, Wolfgang

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up vote 1 down vote accepted

Suppose you're in state $i$. For each $j$, let $X_j$ be an independent Exponential random variable with mean 1.

Now solve $\int_{0}^{T_j}\alpha_{i,j}(t)\ dt=X_j$ for each $i$. Whichever of the $T_j$'s is smallest, you jump from state $i$ to state $j$ at time $T_j$.

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Thank you very much for your answer. Do you have a reference (a book or paper) for your answer. I will now apply this procedure in MATHEMATICA. Again, thank you! –  Wolfgang123 May 31 '13 at 5:44
    
No sorry I don't. Something like this has been in the back of my mind for a while. You can check it though: compute the probability that there's a transition from $i$ to $j$ in the time interval $(t,t+dt)$ conditioned that there has been no transition up to time t. –  Anthony Quas May 31 '13 at 6:04
    
I tested it with constant transition intensities alpha and it works fine. For general alpha's as described above, it seems that it does not work correctly. Maybe I make a mistake. However, I will now apply your method to simulate a 3-state model (illness-death model). In this case, the analytical solution is known and will compare it with numerical results. –  Wolfgang123 May 31 '13 at 8:19
    
It works pretty fine with the reduced model. I generalized the model and solved the corresponding Chapman-Kolmogorov equation system and everything works pretty fine. Thank you VERY much, with best wishes Wolfgang –  Wolfgang123 May 31 '13 at 10:29
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