Measure-valued Markov processes and stochastic flows on abstract spaces
Measure-valued Markov processes and stochastic flows on abstract spaces
复制标题
抽象空间上的测值马尔可夫过程和随机流
DOI：
10.1080/10451120422331292216
复制
发表时间：
2004
期刊：
影响因子：
--
通讯作者：
A. Dorogovtsev
中科院分区：
文献类型：
--
作者：
A. Dorogovtsev
考虑Hilbert空间中具有常质量的测度值过程。携带质量的随机流满足系数取决于质量分布的随机微分方程。这个质量分布可以看作是某个解的条件分布。与过滤方程相反，在我们的例子中，随机测量不能扩散：单个粒子不能分裂或变成云。研究了所得测度值过程的马氏结构，并与Fleming-Viot过程进行了比较。
We consider measure-valued processes with constant mass in Hilbert space. The stochastic flow which carries the mass satisfies a stochastic differential equation with coefficients depending on the mass distribution. This mass distribution can be considered as the conditional distribution of the solution of a certain SDE. In contrast to the filtration equation, in our case the random measure cannot diffuse: a single particle cannot break up or turn into clouds. The Markov structure of the measure-valued processes obtained is studied and a comparison with Fleming–Viot processes is presented.