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Related papers: Limit Theorems Associated With The Pitman-Yor Proc…

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In this work, we obtain the central limit theorem for fluctuations of Young diagrams around their limit shape in the bulk of the "spectrum" of partitions of a large integer n (under the Plancherel measure). More specifically, we show that,…

Probability · Mathematics 2007-05-23 L. V. Bogachev , Z. G. Su

We provide a general theorem bounding the error in the approximation of a random measure of interest--for example, the empirical population measure of types in a Wright-Fisher model--and a Dirichlet process, which is a measure having…

Probability · Mathematics 2020-07-07 Han L. Gan , Nathan Ross

The Shannon entropy is a fundamental measure for quantifying diversity and model complexity in fields such as information theory, ecology, and genetics. However, many existing studies assume that the number of species is known, an…

Methodology · Statistics 2026-02-23 Takato Hashino , Koji Tsukuda

We present new, exceptionally efficient proofs of Poisson--Dirichlet limit theorems for the scaled sizes of irreducible components of random elements in the classic combinatorial contexts of arbitrary assemblies, multisets, and selections,…

Probability · Mathematics 2014-01-09 Richard Arratia , Fred Kochman

For a long time, the Dirichlet process has been the gold standard discrete random measure in Bayesian nonparametrics. The Pitman--Yor process provides a simple and mathematically tractable generalization, allowing for a very flexible…

Statistics Theory · Mathematics 2020-01-08 Caroline Lawless , Julyan Arbel

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

Discrete random probability measures and the exchangeable random partitions they induce are key tools for addressing a variety of estimation and prediction problems in Bayesian inference. Indeed, many popular nonparametric priors, such as…

Statistics Theory · Mathematics 2015-03-03 P. De Blasi , S. Favaro , A. Lijoi , R. H. Mena , I. Pruenster , M. Ruggiero

We consider a particle system in continuous time, discrete population, with spatial motion and nonlocal branching. The offspring's weights and their number may depend on the mother's weight. Our setting captures, for instance, the processes…

Probability · Mathematics 2012-10-12 Bertrand Cloez

The two-parameter Poisson-Dirichlet diffusion takes values in the infinite ordered simplex and extends the celebrated infinitely-many-neutral-alleles model, having a two-parameter Poisson-Dirichlet stationary distribution. Here we identify…

Probability · Mathematics 2024-10-16 Robert C. Griffiths , Matteo Ruggiero , Dario Spanò , Youzhou Zhou

The hierarchical Dirichlet process is a discrete random measure used as a prior in Bayesian nonparametrics and motivated by the study of groups of clustered data. We study the asymptotic behavior of the power sum symmetric polynomials for…

Probability · Mathematics 2025-08-29 Shui Feng , J. E. Paguyo

The Gamma-Dirichlet structure corresponds to the decomposition of the gamma process into the independent product of a gamma random variable and a Dirichlet process. This structure allows us to study the properties of the Dirichlet process…

Probability · Mathematics 2011-12-21 Shui Feng , Fang Xu

Pitman~(1999) describes a duality relationship between fragmentation and coagulation operators. An explicit relationship is described for the two-parameter Poisson-Dirichlet laws, with parameters {\footnotesize $(\alpha,\theta)$} and…

Probability · Mathematics 2007-05-23 Man-Wai Ho , Lancelot F. James , John W. Lau

In many applications, a finite mixture is a natural model, but it can be difficult to choose an appropriate number of components. To circumvent this choice, investigators are increasingly turning to Dirichlet process mixtures (DPMs), and…

Statistics Theory · Mathematics 2013-09-03 Jeffrey W. Miller , Matthew T. Harrison

We establish some limit theorems for quasi-arithmetic means of random variables. This class of means contains the arithmetic, geometric and harmonic means. Our feature is that the generators of quasi-arithmetic means are allowed to be…

Statistics Theory · Mathematics 2022-05-09 Yuichi Akaoka , Kazuki Okamura , Yoshiki Otobe

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 consider the problem of learning two families of time-evolving random measures from indirect observations. In the first model, the signal is a Fleming--Viot diffusion, which is reversible with respect to the law of a Dirichlet process,…

Statistics Theory · Mathematics 2014-11-19 Omiros Papaspiliopoulos , Matteo Ruggiero , Dario Spanò

Define the scaled empirical point process on an independent and identically distributed sequence $\{Y_i: i\le n\}$ as the random point measure with masses at $a_n^{-1} Y_i$. For suitable $a_n$ we obtain the weak limit of these point…

Probability · Mathematics 2016-08-16 André Dabrowski , Gail Ivanoof , Rafal Kulik

We establish a large deviation principle for the trajectories of Wiener processes subject to random resets to the origin occurring according to a Poisson process. In addition to the pathwise large deviation principle, we identify the rate…

Probability · Mathematics 2025-12-09 A. V. Logachov , O. M. Logachova , A. A. Yambartsev , K. A. Zaykov

The aim of the paper is to introduce a two-parameter family of infinite-dimensional diffusion processes X(alpha,theta) related to Pitman's two-parameter Poisson-Dirichlet distributions PD(alpha,theta). The diffusions X(alpha,theta) are…

Probability · Mathematics 2010-02-08 Leonid Petrov

We derive large-sample and other limiting distributions of the ``frequency of frequencies'' vector, ${\bf M_n}$, together with the number of species, $K_n$, in a Poisson-Dirichlet or generalised Poisson-Dirichlet gene or species sampling…

Statistics Theory · Mathematics 2023-09-06 Ross Maller , Soudabeh Shemehsavar