(Discrete-measure)-valued stochastic processes

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Stochastic processes indexed by time whose state is a discrete (possibly only countable) measure. Popular in, for example, mathematical models of alleles in biological evolution.

Population genetics keywords, in approximate order of generality and chronology: Fisher-Wright diffusion, Moran process, Viot-Fleming process. Obviously there are many other processes matching this broad description.

For one example, any element-wise-positive vector-valued stochastic process can be made into a discrete-measure-valued process by normalising the state vector to sum to 1. Chinese-restaurant processes as processes in time presumably fit here, although AFAICT the use of these processes in the literature is usually not the time-evolving construction, but rather the infinite-time limit of such a process, which is confusing nomenclature.

If the process does not take values in discrete measures, that would be a different notebook, which does not at the moment exist;

The Dirichlet process, despite its name is not usually sampled as a time process and in any case has boring dynamics. However, it does I believe have time-indexed extensions (Griffin and Steel 2006; Dunson and Park 2008)


Asselah, Amine, Pablo A. Ferrari, and Pablo Groisman. 2011. β€œQuasistationary Distributions and Fleming-Viot Processes in Finite Spaces.” Journal of Applied Probability 48 (2): 322–32.
Donnelly, Peter, and Thomas G. Kurtz. 1996. β€œA Countable Representation of the Fleming-Viot Measure-Valued Diffusion.” The Annals of Probability 24 (2): 698–742.
Dunson, David B, and Ju-Hyun Park. 2008. β€œKernel Stick-Breaking Processes.” Biometrika 95 (2): 307–23.
Ethier, S. N., and R. C. Griffiths. 1993. β€œThe Transition Function of a Fleming-Viot Process.” The Annals of Probability 21 (3): 1571–90.
Ethier, S. N., and Thomas G. Kurtz. 1993. β€œFleming–Viot Processes in Population Genetics.” SIAM Journal on Control and Optimization 31 (2): 345–86.
Fleming, Wendell H, and Michel Viot. 1979. β€œSome Measure-Valued Markov Processes in Population Genetics Theory.” Indiana University Mathematics Journal 28 (5): 817–43.
Griffin, J. E., and M. F. J. Steel. 2006. β€œOrder-Based Dependent Dirichlet Processes.” Journal of the American Statistical Association 101 (473): 179–94.
Konno, N., and T. Shiga. 1988. β€œStochastic Partial Differential Equations for Some Measure-Valued Diffusions.” Probability Theory and Related Fields 79 (2): 201–25.
Marzen, S. E., and J. P. Crutchfield. 2020. β€œInference, Prediction, and Entropy-Rate Estimation of Continuous-Time, Discrete-Event Processes.” arXiv:2005.03750 [Cond-Mat, Physics:nlin, Stat], May.
Moran, P. a. P. 1958. β€œRandom Processes in Genetics.” Mathematical Proceedings of the Cambridge Philosophical Society 54 (1): 60–71.
Nowak, Martin A. 2006. Evolutionary Dynamics: Exploring the Equations of Life. Belknap Press of Harvard University Press.

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