Abstract
We study the limit behaviour of a class of random walk models taking values in the standard d-dimensional simplex. From an interior point z, the process chooses one of the vertices of the simplex, with probabilities depending on z, and then the particle randomly jumps to a new location z′ on the segment connecting z to the chosen vertex. In some special cases, using properties of the Beta distribution, we prove that the limiting distributions of the Markov chain are Dirichlet. We also consider a related history-dependent random walk model in [0, 1] based on an urn-type scheme. We show that this random walk converges in distribution to an arcsine random variable.
Original language | English |
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Pages (from-to) | 409-428 |
Number of pages | 20 |
Journal | Journal of Applied Probability |
Volume | 57 |
Issue number | 2 |
DOIs | |
Publication status | Published - 16 Jul 2020 |
Keywords
- Dirichlet distribution
- iterated random functions
- Keywords: Random walks in simplexes
- stick-breaking process