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We construct a two-parameter family of Feller diffusions on the set of open subsets of $(0,1)$ that arise as diffusive limits of two-parameter ordered Chinese Restaurant Process up-down chains. The diffusions we construct are natural…

Probability · Mathematics 2021-02-09 Kelvin Rivera-Lopez , Douglas Rizzolo

We establish scaling limit theorems for the up-down ordered Chinese restaurant processes (oCRPs) of Rogers and Winkel as processes in a space of interval partitions. As previously conjectured, the limits are self-similar diffusions…

Probability · Mathematics 2025-12-09 Quan Shi , Matthias Winkel

The Chinese restaurant process is a basic sequential construction of consistent random partitions. We consider random point measures describing the composition of small blocks in such partitions and show that their scaling limit is given by…

Probability · Mathematics 2025-10-09 Oleksii Galganov , Andrii Ilienko

We construct a pair of related diffusions on a space of interval partitions of the unit interval $[0,1]$ that are stationary with the Poisson-Dirichlet laws with parameters (1/2,0) and (1/2,1/2) respectively. These are two particular cases…

Probability · Mathematics 2017-03-23 Noah Forman , Soumik Pal , Douglas Rizzolo , Matthias Winkel

We study composition-valued continuous-time Markov chains that appear naturally in the framework of Chinese Restaurant Processes (CRPs). As time evolves, new customers arrive (up-step) and existing customers leave (down-step) at suitable…

Probability · Mathematics 2020-06-12 Dane Rogers , Matthias Winkel

We introduce diffusions on a space of interval partitions of the unit interval that are stationary with the Poisson-Dirichlet laws with parameters $(\alpha,0)$ and $(\alpha,\alpha)$. The construction has two steps. The first is a general…

Probability · Mathematics 2019-10-18 Noah Forman , Soumik Pal , Douglas Rizzolo , Matthias Winkel

An up-down chain is a Markov chain in which each transition is a two-step process that moves up to a larger object and then back down to an object of the original size. The first goal of this paper is to present a general framework for…

Probability · Mathematics 2025-12-24 Valentin Féray , Kelvin Rivera-Lopez

We investigate the random permutation matrices induced by the Chinese restaurant processes with $(\alpha,\theta)$-seating. When $\alpha=0,\theta>0$, the permutations are those following Ewens measures on symmetric groups, and have been…

Probability · Mathematics 2024-12-20 Jaime Garza , Yizao Wang

Multisets are like sets, except that they can contain multiple copies of their elements. If there are $n_i$ copies of $i$, $1\leq i\leq t$, in multiset $M_t$, then there are $\binom{n_1+\cdots+n_t}{n_1,\ldots, n_t}$ possible permutations of…

Probability · Mathematics 2026-02-17 Dudley Stark

Given a growth rule which sequentially constructs random permutations of increasing degree, the stochastic process version of the rencontre problem asks what is the limiting proportion of time that the permutation has no fixed points…

Probability · Mathematics 2022-09-27 Alexander Gnedin , Dudley Stark

The Pitman-Yor, or Chinese Restaurant Process, is a stochastic process that generates distributions following a power-law with exponents lower than two, as found in a numerous physical, biological, technological and social systems. We…

Disordered Systems and Neural Networks · Physics 2015-05-13 Bruno Bassetti , Mina Zarei , Marco Cosentino Lagomarsino , Ginestra Bianconi

We study a Markov process constructed from the P\'olya sum process, which yields a kind of spatial version of the Chinese restaurant process, where each 'table' is assigned a 'location'. This construction firstly allows a definition of…

Probability · Mathematics 2013-06-20 Mathias Rafler

We investigate a disordered variant of Pitman's Chinese restaurant process where tables carry i.i.d. weights. Incoming customers choose to sit at an occupied table with a probability proportional to the product of its occupancy and its…

Probability · Mathematics 2024-05-06 Jakob E. Björnberg , Cécile Mailler , Peter Mörters , Daniel Ueltschi

In previous work, we constructed Fleming--Viot-type measure-valued diffusions (and diffusions on a space of interval partitions of the unit interval $[0,1]$) that are stationary with the Poisson--Dirichlet laws with parameters…

Probability · Mathematics 2021-01-26 Noah Forman , Soumik Pal , Douglas Rizzolo , Matthias Winkel

We construct a stationary Markov process corresponding to the evolution of masses and distances of subtrees along the spine from the root to a branch point in a conjectured stationary, continuum random tree-valued diffusion that was…

Probability · Mathematics 2018-04-05 Noah Forman , Soumik Pal , Douglas Rizzolo , Matthias Winkel

We give a pathwise construction of a two-parameter family of purely-atomic-measure-valued diffusions in which ranked masses of atoms are stationary with the Poisson-Dirichlet$(\alpha,\theta)$ distributions, for $\alpha\in (0,1)$ and…

Probability · Mathematics 2022-07-25 Noah Forman , Douglas Rizzolo , Quan Shi , Matthias Winkel

We establish a quenched functional central limit theorem for the total number of components of random partitions induced by Chinese restaurant process with parameters $(\alpha,\theta), \alpha\in(0,1), \theta>-\alpha$. With $P_j$ denoting…

Probability · Mathematics 2026-04-08 Yizao Wang

We propose a unified approach to establishing diffusion approximations for queues with impatient customers within a general framework of scaling customer patience time. The approach consists of two steps. The first step is to show that the…

Probability · Mathematics 2015-10-06 Junfei Huang , Hanqin Zhang , Jiheng Zhang

It was recently shown that arbitrary first-order models canonically extend to models (of the same language) consisting of ultrafilters. The main precursor of this construction was the extension of semigroups to semigroups of ultrafilters, a…

Logic · Mathematics 2013-10-18 Denis I. Saveliev

Dirichlet process mixture (DPM) models tend to produce many small clusters regardless of whether they are needed to accurately characterize the data - this is particularly true for large data sets. However, interpretability, parsimony, data…

Machine Learning · Computer Science 2018-02-16 Jun Lu , Meng Li , David Dunson
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