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$P$ is a one-dimensional Markov stochastic process that runs on time interval $[0, t_f]$. I know its transition function: $P(0) = x_0$ and for any $0 \le t_a < t_b \le t_f$, the function $f(x_b | x_a, t_a, t_b)$ describes the probability that $P(t_b) = x_b$ given that $P(t_a) = x_a$ (so $f$ is a density function in its first parameter).

Now, let $I$ be the random variable described by $\int_0^{t_f} P(s) ds$ for a random realization of $P$. Is it possible to find a density function for $I$ in terms of $f$ and $x_0$?

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Is it a Markov process? If not, you might need more than that to describe the process. – Robert Israel Nov 11 '12 at 18:58
    
Ah, yes it is, thank you. I just edited that detail into the post. – user21816 Nov 11 '12 at 19:10
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The following paper might help you identify situations where there is an explicit expression for the moment generating function of the integral arxiv.org/abs/0710.1599 (Albanese and Lawi, 2007.) – Paul Tupper Nov 12 '12 at 18:27

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