Homogeneous random measures and a weak order for the excessive measures of a Markov process
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- by P. J. Fitzsimmons PDF
- Trans. Amer. Math. Soc. 303 (1987), 431-478 Request permission
Abstract:
Let $X = ({X_t}, {P^x})$ be a right Markov process and let $m$ be an excessive measure for $X$. Associated with the pair $(X, m)$ is a stationary strong Markov process $({Y_t}, {Q_m})$ with random times of birth and death, with the same transition function as $X$, and with $m$ as one dimensional distribution. We use $({Y_t}, {Q_m})$ to study the cone of excessive measures for $X$. A "weak order" is defined on this cone: an excessive measure $\xi$ is weakly dominated by $m$ if and only if there is a suitable homogeneous random measure $\kappa$ such that $({Y_t}, {Q_\xi })$ is obtained by "birthing" $({Y_t}, {Q_m})$, birth in $[t, t + dt]$ occurring at rate $\kappa (dt)$. Random measures such as $\kappa$ are studied through the use of Palm measures. We also develop aspects of the "general theory of processes" over $({Y_t}, {Q_m})$, including the moderate Markov property of $({Y_t}, {Q_m})$ when the arrow of time is reversed. Applications to balayage and capacity are suggested.References
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Additional Information
- © Copyright 1987 American Mathematical Society
- Journal: Trans. Amer. Math. Soc. 303 (1987), 431-478
- MSC: Primary 60J45; Secondary 60G57, 60J55
- DOI: https://doi.org/10.1090/S0002-9947-1987-0902778-5
- MathSciNet review: 902778