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Abstract Given a finite strongly connected directed graph $G=(V, E)$ , we study a Markov chain taking values on the space of probability measures on V. The chain, motivated by… Click to show full abstract
Abstract Given a finite strongly connected directed graph $G=(V, E)$ , we study a Markov chain taking values on the space of probability measures on V. The chain, motivated by biological applications in the context of stochastic population dynamics, is characterized by transitions between states that respect the structure superimposed by E: mass (probability) can only be moved between neighbors in G. We provide conditions for the ergodicity of the chain. In a simple, symmetric case, we fully characterize the invariant probability.
Keywords:
process graphs;
transport process;
graphs limiting;
limiting distributions;
probability;
chain
Journal Title: Journal of Applied Probability
Year Published: 2022
Link to full text (if available)
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Journal Title: Journal of Applied Probability
Year Published: 2022
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!