Artikel,

A Path Decomposition for Markov Processes

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The Annals of Probability, 6 (2): 345--348 (1978)

Zusammenfassung

Let $X = \X_t, t > 0\$ be a right continuous strong Markov process with state space $E$; let $f$ be a continuous real valued function on $E E$; and let $M$ be the time at which the process $\f(X_t-, X_t)\$ achieves its (last) ultimate minimum. Then conditional on $X_M$ and the value of this minimum, the process $\X_M + t\$ is Markov and (conditionally) independent of events before $M$.

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  • @peter.ralph

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